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• Small variants in mtDNA Canary Islands - WGS Oxford Nanopore Technologies (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005677

• Radiation-Related Genomic Profile of Papillary Thyroid Cancer after the Chernobyl Accident

  The April 26, 1986 accident at the Chernobyl nuclear power plant in northern Ukraine resulted in the release of radioactive contaminants, which were deposited in the surrounding areas in Ukraine, Belarus, and Russia. The main radiation-related health effect resulting from these exposures is the increased occurrence of thyroid cancer among individuals who were children at the time of the accident or born shortly thereafter. The purpose of this study was to conduct a comprehensive genomic landscape analysis of papillary thyroid tumors arising in individuals who were exposed as children to radioactive iodine (I-131) from the Chernobyl nuclear power plant accident.

  Study phs001134

• Germline RUNX1 Variation and Predisposition to Childhood Acute Lymphoblastic

  Somatic mutations of RUNX1, which encodes the myeloid and lymphoid transcriptional factor RUNX1, are common in both B- and T- acute lymphoid leukemia (ALL) and are associated with poor prognosis of T-ALL. However, there has been no comprehensive investigation of the pattern or prevalence of RUNX1 germline mutation in both B- and T-ALL. Here we report germline RUNX1 variants in 1.23% of B-ALL and 2.11% of T-ALL, identifying 31 unique variants in 62 B-ALL and 18 unique variants in 26 T-ALL children. The majority of frameshift and nonsense variants affected RUNX1 function in transcriptional regulation, hematopoiesis, and cellular proliferation. We identified JAK3 as the most frequent somatic mutation in T-ALL with RUNX1 variants. These results not only identify RUNX1 as a leukemia predisposition gene but also further underline the importance of germline genetic variants to the development of ALL

  Study EGAS00001005403

• cfDNA in Hereditary And High-Risk Malignancies (CHARM)

  Our goal is to improve early cancer detection by developing a blood test to predict cancer development in carriers using circulating DNA. As carriers develop cancer, they may have pre-cancerous cells which release this DNA into the blood (cell-free DNA; cfDNA), which can be detected with novel genetic technologies. We propose to use three complementary cfDNA assays:shallow whole genome sequencing (sWGS), Liquid-Biopsy Sequencing (LB-Seq) and Cell-free Methylated DNA Immunoprecipitation and High-throughput Sequencing (cfMeDip-Seq) for early cancer detection.

  Study EGAS00001006539

• A Genome-Wide Association Study in Patients Experiencing Breast Events While Receiving Adjuvant Aromatase Inhibitors for Early Breast Cancer on NCIC CTG Trial MA.27

  Source of patients:The source of the patients for this genome-wide case-control study was MA.27, which was conducted as a multi-cooperative group effort under the auspices of the NCI Breast Cancer Intergroup of North America. The NCIC Clinical Trials Group (CTG) serves as the coordinating group, with participation by the NCI-sponsored North Central Cancer Treatment Group, Eastern Cooperative Oncology Group (ECOG), Southwest Oncology Group, and Cancer and Leukemia Group B (CALGB). MA.27 involved postmenopausal women with histologically confirmed and completely resected invasive breast cancer with surgical margins clear of invasive carcinoma in the following TMN categories (AJCC Version 6): pT1, pT2, pT3; pNx, pN0, pN1, pN2, pN3 (only when the sole basis is presence of 10 or more involved axillary nodes); MO. The primary tumor must have been estrogen receptor (ER) and/or progesterone receptor positive. Patients were stratified by lymph node status at diagnosis, prior adjuvant chemotherapy, and trastuzumab use and were randomized to 5 years of adjuvant therapy with anastrozole or exemestane. The trial was activated on May 26, 2003, and reached its accrual objectives on July 31, 2008, after the randomization of 6827 North American patients, with the majority (79%) providing DNA and consent for genetic testing. Non-North American patients were also entered by the International Breast Cancer Study Group but they did not contribute DNA. From 2003 to December 21, 2004, patients also underwent a second randomization to celecoxib 400 mg twice daily or placebo but, after the entry of 1,622 patients, this treatment was discontinued because of reports of increased cardiovascular risk associated with celecoxib. The final results of this study have been published, see Goss et al., 2013 (23358971). The patients in this analysis came from three cohorts: Cohort 1 consisted of 870 patients genotyped on the Illumina Human610-Quad BeadChip studied in a GWAS with the phenotype of musculoskeletal adverse event, see Ingle et al., 2010 (20876420), Cohort 2 consisted of 882 patients genotyped on the Illumina OmniExpress platform studied in a GWAS with the phenotype of fragility fractures, see Liu et al., 2014 (25148458), and the remaining 2913 patients were genotyped with the Illumina OmniExpressExome platform.

  Study phs001043

• Development and Validation of a Disability Severity Index for Charcot-Marie-Tooth Disease (CMT)

  In Charcot-Marie-Tooth Disease (CMT) or inherited neuropathy research studies, it is the researcher who has selected what they believe to be important markers of impairment in function in patients. For example, it has been inferred that the wearing of ankle-foot-orthosis (AFOs), the use of walking aids such as canes, or the use of wheelchairs, are appropriate markers for “mild”, “moderate” or “severe” disability, respectively. Whether patients agree with this classification is unknown. By understanding what patients classify as mild, moderate and severe disability in CMT, we will know what our treatments need to target, to have a meaningful impact on the patients' functional status. Primary objective: The purpose of this study is to compare patient and healthcare provider impressions of what constitutes mild, moderate and severe disability in CMT. Target population: 200 patients who have self-registered at the Inherited Neuropathy Consortium Contact Registry, a web-based contact registry developed and supported by the Data Management and Coordinating Center (DMCC) for the Rare Diseases Clinical Research Consortium (RDCRN), located at the University of South Florida, and 200 health care professionals attending conferences about CMT, such as the 4th International CMT Consortium to be held in Potomac, Maryland, June 29-July 1, 2011 and the MDA Clinic Directors meeting in Las Vegas, NV March 4-7, 2012. Methods: A brief, anonymous, 20-item survey, in which we measure what the physician and the patient think are important indicators of disability in CMT, will be distributed by paper to 200 health care professionals, and via an online link to 200 patients self-registered with the RDCRN contact registry. Out of the 200 patients, approximately 25 patients will be requested to take the survey twice in a 2 to 4 week period. Analysis: We will measure the agreement between items in the physician and patient groups, and use items with high agreement in a Disability Severity Index.

  Study phs001295

• SDH_deficient_renal_tumours___RNA_

  Succinate dehydrogenase (SDH) deficient renal cancers are a rare and understudied subtype of renal cancer. As such they represent an unmet need in kidney cancer research. Here, we seek to describe the genomics and transcriptomics of SDH deficient renal cancers by sequencing five such tumours. We document their mutational burden, define driver mutations, demonstrate typical patterns of structural variants, and estimate the cell of origin and cellular composition.

  Study EGAS00001004103

• Pancreatic, Small-intestinal and Pulmonary Neuroendocrine Tumors

  Purpose: The primary origin of neuroendocrine tumor metastases can be difficult to determine by histopathology alone, but is critical for therapeutic decision making. DNA methylation-based profiling is now routinely used in the diagnostic workup of brain tumors. This has been enabled by the availability of cost-efficient array-based platforms. We have extended these efforts to augment histopathological diagnosis in neuroendocrine tumors. Experimental Design and Results: We compiled data of 69 small-intestinal, pulmonary, and pancreatic neuroendocrine tumors. These data were used to build a ridge regression calibrated random forest classification algorithm (NEN-ID) that predicts the origin of tumor samples with high accuracy (> 95%). The model was validated during 3x3 nested cross validation and tested in a local (n=26) and external (n=172) cohort. In addition, we show that our diagnostic approach is robust across a range of possible confounding experimental parameters such as tumor purity and array quality. A software infrastructure and online user interface was built to make the model available to the scientific community. Conclusions: This DNA methylation-based prediction model can be used in the workup for patients with neuroendocrine tumors of unknown primary. To facilitate validation and clinical implementation, we provide a user-friendly, publicly available web-based version of NEN-ID.

  Study EGAS00001004878

• Spatial and Temporal Homogeneity of Driver Mutations in Diffuse Intrinsic Pointine Glioma

  Diffuse Intrinsic Pontine Gliomas (DIPG) are deadly pediatric brain tumors where needle biopsies help guide diagnosis and targeted therapies. To address spatial heterogeneity, we analyzed 134 specimens from various neuroanatomical structures of whole autopsy brains from nine DIPG patients. Evolutionary reconstruction indicates histone 3 (H3)K27M – including novel H3.2K27M - mutations potentially arise first and are invariably associated with specific, high-fidelity obligate partners throughout the tumor and its spread, from diagnosis to end-stage disease, suggesting mutual need for tumorigenesis. These H3K27M ubiquitously-associated mutations involve alterations in TP53 cell-cycle (TP53/PPM1D) or specific growth factor pathways (ACVR1/PIK3R1). Later oncogenic alterations arise in sub-clones and often affect the PI3K pathway. Our findings are consistent with early tumor spread outside the brainstem including the cerebrum. The spatial and temporal homogeneity of driver mutations in DIPG implies they will be captured by limited biopsies and emphasizes the need to develop therapies specifically targeting obligate oncohistone partnerships.

  Study EGAS00001001654

• Risk Assessment of Cerebrovascular Events (RACE) Study

  This study includes 1,220 cases with young onset stroke (stroke before age 60 years) who are participants of the larger RACE study. Risk Assessment of Cerebrovascular Events (RACE) is an on-going existing case-control study of stroke now involving over 5000 imaging confirmed cases of stroke and 5000 controls, recruited from seven centers in Pakistan. The study is aimed to investigate the genetic, biomarker and lifestyle determinants of stroke and its subtypes. Cases are eligible for inclusion in the study if they: (i) are aged at least 18 years; (ii) present with a sudden onset of neurological deficit respecting a vascular territory with sustained deficit at 24 hours verified by medical attention within 72 hours after onset (onset is defined by when the patient was last seen normal and not when found with deficit); and (iii) the diagnosis is supported by CT/MRI; and (iv) present with a Modified Rankin Score < 2 prior to the stroke. Findings from patient's history, 12-lead ECG and CT or MRI of the brain. The mandatory procedures for inclusion in this investigation are: (i) clinical verification of cerebrovascular event within 72 hours of onset; (ii) neuroimaging CT (non-contrast) or MRI (MRI is not a mandatory investigation but recorded whenever ordered by the attending physician); and (iii) 12-lead ECG. All other ancillary investigations ordered by the attending physician are recorded as well. The TOAST classification method is used to classify ischemic stroke based on aetiology whereas the Oxfordshire classification is used to classify stroke neuro-anatomically. Control participants for this subset of young onset stroke were individuals enrolled in the Pakistan Risk of Myocardial Infarction Study (PROMIS), a case-control study of acute MI based in Pakistan. RACE capitalizes on the genetic data (including information on GWAS) that has already been collected from the healthy participants enrolled in PROMIS. RACE and PROMIS share similar methodology of recruitment. Participants from both these investigations are derived from similar catchment areas, hence providing an attractive opportunity for RACE to utilize PROMIS controls as common controls for genetic investigations. Controls in PROMIS were recruited following procedures and inclusion criteria as adopted for RACE cases. In order to minimize any potential selection biases, PROMIS controls selected for this stroke substudy were frequency matched to RACE cases based on age and gender and were recruited in the following order of priority: (1) non-blood related or blood related visitors of patients of the out-patient department; (2) non-blood related visitors of stroke patients; (3) patients of the out-patient department presenting with minor complaints (e.g. back pain, minor gastric complaints). Control subjects from the PROMIS study were genotyped at the Wellcome Trust Sanger Institute on the Illumina 660W Quad array. The Center for Non-Communicable Diseases, Pakistan, serves as the coordinating center for both RACE and PROMIS. More information on these research investigations can be found at www.cncdpk.com. This young onset stroke component to the RACE study was funded through the Gene Environment Association Studies initiative (GENEVA, www.genevastudy.org as one of three studies designed to assess the genetics of young onset stroke and modification of genetic effects by smoking. GENEVA is part of the trans-NIH Genes, Environment, and Health Initiative (GEI). Genotyping of 1,220 young onset stroke cases was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to stroke through large-scale genome-wide association studies of cases and controls recruited within Pakistan. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000456

• Rare germline sequence variants, copy number variations, expression alterations, methylation variations and disease susceptibility in familial melanoma

  Although a number of high-risk melanoma genes have been identified, they account for melanoma risk in less than 40% of melanoma-prone families. The major goals of our research are to identify novel high-penetrance genes for familial melanoma in melanoma-prone families without known mutations and to identify modifier factors, including genetic and epigenetic, in melanoma-prone families with and without known major mutations. We are using whole exome sequencing to identify additional high-risk susceptibility genes and using targeted sequencing to follow up on the top genes in additional family members and in population-based melanoma cases and controls. We are also using RNASeq to investigate genome-wide allele-specific expression and eQTLs in these families to identify genes with expression alteration, which will provide additional information for gene discovery. In addition, we also conducted genome-wide copy number variation (CNV), methylation, and miRNA expression profiling analyses in our melanoma families with the goal of identifying genetic and epigenetic factors as disease modifiers.

  Study phs001177

• California Pacific Medical Center Research Breast Health Cohort

  Description of Cohort: The California Pacific Medical Center (CPMC) Breast Health Cohort is a cohort study based at CPMC and is linked to the San Francisco Mammography Registry, one of the sites of the NCI-funded Breast Cancer Screening Consortium (U01CA063740). CPMC is a community hospital in San Francisco, which has one of the highest volumes for mammography in San Francisco. Between September 2004 and June 2007, >90,000 mammograms were performed at CPMC. The CPMC breast health cohort collects demographic and risk factor data on women receiving mammography through participation in the San Francisco Mammography Registry, as part of the Breast Cancer Screening Consortium (U01CA063740). The SFMR database collects information from all sources, including a questionnaire on demographic and risk factor information, the clinical results of the breast examination, the measures of breast density by Dr. John Shepherd and the women who agreed to donate a blood sample. By merging these various sources of information we have very efficiently developed a large sample of women who have donated blood and have had a measure of mamographic density. Blood Collection: Dr. Steve Cummings is leading an effort to collect and archive blood samples from women who are receiving mammography screening. All women who are sent for a screening mammogram at CPMC are considered eligible. Since the cohort began collecting blood samples in July 2004 until June 2007, samples have been collected from over 11,000 women. Measurement of Breast Density: Dr. John Shepherd is currently measuring breast density in a large fraction of the cohort using an automated approach with single X-ray absorptiometry. Dr. Shepherd has established a link with the CPMC mammography center that allows him to collect routine digital mammography information. Using the data from the mammogram, Dr. Shepherd and his group have developed the single X-ray absorptiometry (SXA) technique for measuring density which is described in more detail below. The table demonstrates the distribution of demographic variables and some breast cancer risk factors of women who donated blood and had a breast density measurement in the CPMC breast health cohort. Nearly 80% of the participants are Caucasian and most of the women are post-menopausal with a median age of ~52. Since it will be difficult to accrue a large enough sample from each ethnic group, our study will focus only on Caucasian women. Table: Demographic variables, reproductive history and family history of breast cancer among 2962 women participating in the CPMC cohort study who contributed blood samples between 1994-1997. Variable Median/Percentage Age (Median/IQR) 52 (46-59) Ethnicity Caucasian/White 0.76 Asian/Pacific Islander 0.141 Hispanic 0.029 Mixed Race/Ethnicity 0.039 African American/Black 0.022 American Indian 0.001 Other 0.009 First degree relative with breast cancer 0.17 Age at first birth Nulliparous 0.39 Age<20 0.043 Age>40 0.032 Age<30, ≥20 0.251 Age>30, ≤40 0.282 Measurement of Breast Density in Cohort: Measurement of breast density is accomplished using an automated technique for all mammograms obtained by Dr. Shepherd using Single X-Ray absorptiometry (SXA). SXA measurement of breast density is done on approximately 30% of all screening mammograms. Below we describe the method for measurement of breast density by SXA by Dr. Shepherd's group and its validation and association with breast cancer. As we demonstrate below, breast density, as measured by SXA, is an automated, highly reproducible measure of the density of breast tissue and is associated with breast cancer risk. SXA for Quantifying Breast Density: Single x-ray absorptiometry (SXA) was initially developed for measuring bone density. SXA can determine the fraction of each of two densities simultaneously using the fact the sample is a constant thickness, the thickness in known, and the total attenuation is known. In applying this technique to breast density, we assume a two compartment model: fat and non-fatty (fibroglandular tissue). We use a reference material composed of various concentrations of two materials: one which is the same density as fat and another which is the same density as fibroglandular tissue. The reference material (phantom) is placed in the X-ray field with each mammogram. We have been able to implement this in a way that is unintrusive to the patient and technologist at CPMC. Assuming this two-compartment model and a constant known breast thickness, we can then calculate the percent density at any region of the breast based on the assumption that % pixel grey-scale is proportion to the mass fractions of breast fat and lean tissue. If reference materials (a phantom) of fat and fibroglandular tissue are imaged with the patient's breast and the reference materials have the same thickness as the patient's breast, then the breast's grey-scale values can be converted to fat/fibroglandular mass fractions by interpolating between those two references. The total percent density is found by averaging the volume fraction over all breast pixels. The phantom being used for breast density assessment at CPMC began to be used in September 2004. The phantom does not have to be manipulated by the technologist and stays attached on the mammography device during standard craniocaudal (CC) views. Thus it creates minimal to no interference with the clinical mammogram. Reproducibility of breast density measures: Traditional measures of mammographic density require some human interpretation. A human reader outlines the area perceived to be dense and a computer then calculates the percent area outlined as a percent of the entire image. Thus, while traditional mammographic density is associated with breast cancer risk, it has some limitations. In a study by Drs. Shepherd, Kerlikowske, et al., the correlation coefficient (Pearson's R) between different readers was 0.8-0.9. In contrast to the traditional mammographic density measurement, the SXA measurement is fully automated and, therefore, the reproducibility of the measurement is higher. Dr. Shepherd and colleagues have performed a replication study of SXA as a measurement of breast density. They have estimated the correlation coefficient of the SXA measurement of breast density to be >0.98. Thus, as expected for an automated measure, SXA is a highly reproducible measure of mammographic breast density. Drs. Shepherd and Kerlikowske have recently analyzed the association between breast cancer risk and breast density as measured by SXA (Shepherd et al., Cancer Epi Biomarkers and Prev, 2011, PMID: 21610220). They found that women in the highest quintile of % volumetric density had an odds ratio of 4.1 (95% CI: 2.3 - 7.2) for breast cancer risk compared to women in the lowest quintile of volumetric density. Thus volumetric density appears to be a highly reproducible, automated measure of breast cancer.

  Study phs000395

• Frequent germline mutations of HAVCR2 in sporadic subcutaneous panniculitis-like T-cell lymphoma.

  Subcutaneous panniculitis-like T-cell lymphoma (SPTCL) is a rare subtype of peripheral T-cell lymphoma affecting younger cases and associated with hemophagocytic lymphohistiocytosis. To clarify the molecular pathogenesis of SPTCL, we analyzed paired tumor and germline DNAs from 13 patients by whole exome sequencing.

  Dataset EGAD00001004795

• Next generation sequencing of diffuse intrinsic pontine glioma samples to identify recurrent mutations, variations, and expression patterns to define novel therapies

  Diffuse intrinsic pontine glioma (DIPG) is an extremely rare (~350 cases/year) and universally fatal childhood brain cancer. Standard clinical strategies such as chemotherapy and radiotherapy show only transient improvement in patient condition and result in negligible change in survival, DIPG remains at below 1% survival after 5 years. Prioritization of panobinostat through previous cooperative work resulted in a phase 1 clinical trial. Nonetheless, new therapies for DIPG must be identified to further dramatically change the statistics for DIPG. To identify novel therapy strategies for DIPG, we performed whole exome(16 new samples, 22 previously published samples, 38 in total with 26 matched normal) and RNA deep sequencing (17 new samples, 11 previously published samples) on a cohort of new patient samples. Sequencing results aid in the identification of recurrent mutations/variations and endotypic expression profiling to identify new therapeutic and treatment strategies for DIPG.

  Study phs001526

• Genetic Heterogeneity of the familial gastric neuroendocrine tumors (2018-06-06)

  Gastric neuroendocrine tumors (gNETs) occur with an estimated frequency of 2 per 100,000 in the general population. Type I gastric neuroendocrine tumors (NETs) represent the 75% of gNTEs and arise from gastric enterochromaffin-like (ECL) cells. They have late age of onset and usually benigh course. Classically, hypergastrinemia in patients who have autoimmune atrophic gastritis, causes hyperplasia of gastric ECL cells that progresses into type I gastric NETs and parietal cell (PC) destruction. The genetic bases in families with this disease are unknown. We performed an exome sequencing study of an atypical aggressive familial gNETs case (with early age onset, nodal infiltrations and gastric adenocarcinomas) that followed a recessive model. We identified a deleterious mutation in homozygosis in the ATP4A gene, which encodes the proton pump responsible for acid secretion by gastric parietal cells. This mutation lead to achlorhydria first, and hypergastrinemia and gNET developing as consequence (Calvete et al. 2014). Recently, two more families with gNETs, classical clinical traits and recessive model have been studies by WES but we didn't find any mutation in the ATP4a gene. However, putative mutations affecting genes that contribute to the development and the integrity of PC have been found suggesting that genetic alterations associated to this disorder target to a unique cell type (parietal cells). In order to cinfirm this hypothesis, it is necessary the search for new genes implicated in the gNETs, more familial cases are needed to be studied. We have identified four more new familial gNETs cases. Here, we propose their study by WES. The first family is formed by thress siblings with gNETs. The other families include two siblings with gNETs. 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 2018-06-06.

  Dataset EGAD00001004153

• Exome-sequencing of two UFM individuals and their Fragile X family members.

  Fragile X syndrome (FXS) is a monogenic neurodevelopmental disease often caused by a CGG triplet expansion in the 5’UTR of the FMR1 gene, which results in DNA methylation of the FMR1 promoter and its transcriptional silencing. Exceptional healthy individuals named "unmethylated full mutation (UFM)" have been identified in the families of FX patients. They carry an expanded CGG repeat, but show normal FMR1 epigenetic configuration and expression. In this study we performed exome-sequencing of two UFM individuals and their family members to identify possible genetic mutations responsible for the escape of silencing in the unmethylated full mutation (UFM) phenotype.

  Study EGAS00001001737

• NHGRI GREGoR Consortium: Genomics Research to Elucidate the Genetics of Rare Disease

  The NHGRI GREGoR (Genomics Research to Elucidate the Genetics of Rare Disease) Consortium was established in June 2021 with the goal of developing novel tools and approaches to advance the discovery of the genetic basis of rare conditions. Numerous types of molecular data are generated in GREGoR and available on the AnVIL cloud platform via dbGaP application, including short- and long-read genome and exome sequencing, transcriptomics, metabolomics, methylomics, and proteomics. De-identified clinical and demographic data is obtained, with a focus on standardized ontologies.Visit the GREGoR Consortium data webpage for summary information about the GREGoR Dataset, including numbers of participants and data types, methods documentation, and Release Notes. The Consortium comprises five Research Centers (RCs - see below), a Data Coordinating Center (DCC), and various partner members and external collaborators.Baylor College of Medicine Research Center (BCM-GREGoR) The Baylor College of Medicine GREGoR program, which is part of the GREGoR consortium, enrolls individuals, families, and cohorts with suspected rare disease across a range of syndromic and non-syndromic phenotypes. Subjects are enrolled from national and international collaborating physician referrals. Subjects provide written informed consent for future re-contact. Data generated and shared include family structure, detailed phenotypes, exome or short-read genome data, and in some cases long-read genome or RNA-sequencing, and these are shared upon completion of standard quality control checks and annotation. Broad Institute (Broad) The Broad Center for Mendelian Genomics, part of the GREGoR consortium uses next-generation sequencing (exome, genome, transcriptome, and long read sequencing), computational approaches, and functional studies to discover the variants and genes that underlie Mendelian conditions with a particularly focus on neuromuscular, neurodevelopmental, and syndromic phenotypes. Samples come from collaborators and direct enrollment through the Rare Genomes Project and we are committed to rapid data sharing without an embargo period. University of California, Irvine (UCI-GREGoR) To accelerate the pace of Mendelian disease gene discovery and clinical implementation, we propose a Mendelian Genomics Research Center, part of the GREGoR Consortium, leveraging the broad pediatric and adult clinical and research expertise at Children's National Hospital and University of California, Irvine. Our goal is to develop best practices to increase the diagnostic yield of rare diseases, engage the community to reduce health disparities for complex diagnoses, while creating a dataset accessible to all. Our Center will unite world class experts combining basic and translational research with innovative approaches to phenotyping, variant identification and functional investigation of both coding and non-coding sequence changes with the goals of discovering novel Mendelian gene variations and identifying variants not detected on current sequencing pipelines, disambiguating uncertain variants into disease-causing versus benign categorizations, and sharing information by working collaboratively with the GREGoR community.GREGoR Stanford Site (GSS) The goal of the GREGoR Stanford Site (GSS) is to provide a platform for functional genomics research and validation to improve diagnosis in Mendelian disease. Participants included individuals with undiagnosed suspected Mendelian disease who had non-diagnostic exome sequencing and their immediate family members. Participants and their family members provided written, informed consent and biological samples from which DNA, RNA, plasma, fibroblasts, PBMCs and other cell types were generated and stored. Samples from research participants and their immediate family members may have undergone short and long-read genome sequencing, transcriptome sequencing, metabolomics and/or lipidomics profiling, methyl-capture-sequencing and ATAC-sequencing. De-identified clinical data extracted from participant medical records are linked to the samples. University of Washington Center for Rare Disease Research (UW-CRDR) The goals of the University of Washington Center for Rare Disease Research are to: (1) maximize novel gene discovery for Mendelian conditions by recruitment, short- and long-read whole genome sequencing, transcriptome sequencing and analysis of families with rare conditions for which the gene is either unknown or the gene is known but no pathogenic variant can be identified via clinical testing; (2) develop new strategies for gene discovery for Mendelian conditions caused by variants that are difficult to detect using conventional testing strategies, variants of unknown function effect (e.g., regulatory, structural variants) or have unusual modes of inheritance; and (3) implement high-throughput screening and targeted follow-up functional studies to prioritize and validate candidate non-coding variants. De-identified data and phenotypic information are shared via MyGene2, ClinVar, and AnVIL.

  Study phs003047

• Evaluating genetic ancestry and self-reported ethnicity in the context of carrier screening

  Current professional society guidelines recommend genetic carrier screening be offered on the basis of ethnicity, or when using expanded carrier screening panels, they recommend to compute residual risk based on ethnicity. We investigated the reliability of self-reported ethnicity in 9125 subjects referred to carrier screening. We identified several discrepancies between the two sources of self-reported ethnicity and genetic ancestry. As a result, carrier rates and residual risks provided for patient decision-making are impacted if using self-reported ethnicity. We recommend the routine use of pan-ethnic carrier screening panels in reproductive medicine. Furthermore, the use of an ancestry model would allow better estimation of carrier rates and residual risks.

  Study phs001482

• Resolving the Full Spectrum of Human Genome Variation using Linked-Reads

  Large-scale population based analyses coupled with advances in technology have demonstrated that the human genome is more diverse than originally thought. Standard short-read approaches, used primarily due to accuracy, throughput and costs, fail to give a complete picture of a genome. They struggle to identify large, balanced structural events, cannot access repetitive regions of the genome and fail to resolve the human genome into its two haplotypes. Here we describe an approach that retains long range information while harnessing the power of short reads. Starting from only 1ng of DNA, we produce barcoded short read libraries. The use of novel informatic approaches allows for the barcoded short reads to be associated with the long molecules of origin producing a novel datatype known as 'Linked-Reads'. This approach allows for simultaneous detection of small and large variants from a single Linked-Read library. We have previously demonstrated the utility of whole genome Linked-Reads (lrWGS) for performing diploid, de novo assembly of individual genomes. In this manuscript, we show the utility of reference based analysis using a single Linked-Read library for full spectrum genome analysis. We demonstrate the ability of Linked-Reads to reconstruct megabase scale haplotypes and to recover parts of the genome that are typically inaccessible to short reads, including phenotypically important genes such as STRC, SMN1 and SMN2. We demonstrate the ability of both lrWGS and Linked-Read Whole Exome Sequencing (lrWES) to identify complex structural variations, including balanced events, single exon deletions, and single exon duplications. The data presented here show that Linked-Reads provide a scalable approach for comprehensive genome analysis that is not possible using short reads alone.

  Study EGAS00001003121

• Kids First: Genomic Studies of Orofacial Cleft Birth Defects

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). Both childhood cancers and structural birth defects are critical and costly conditions associated with substantial morbidity and mortality. Elucidating the underlying genetic etiology of these diseases has the potential to profoundly improve preventative measures, diagnostics, and therapeutic interventions. WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. The Kids First study of nonsyndromic orofacial cleft birth defects (OFCs) is a whole genome sequencing study of 415 White parent-case trios drawn from ongoing collaborations led by Dr. Mary L. Marazita of the University of Pittsburgh Center for Craniofacial and Dental Genetics, including collaborations with Dr. George Wehby of the University of Iowa, Dr. Jacqueline Hecht of the University of Texas, and Dr. Terri Beaty of Johns Hopkins University. Sequencing was done by the Washington University McDonell Genome Institute. The case in each of the Kids First trios has cleft lip (CL, Figure A), cleft palate (CP, Figure B), or both (CL+CP, Figure C): OFCs are genetically complex structural birth defects caused by genetic factors, environmental exposures, and their interactions. OFCs are the most common craniofacial anomalies in humans, affecting approximately 1 in 700 newborns, and are one of the most common structural birth defects worldwide. On average a child with an OFC initially faces feeding difficulties, undergoes 6 surgeries, spends 30 days in hospital, receives 5 years of orthodontic treatment, and participates in ongoing speech therapy, leading to an estimated total lifetime treatment cost of about $200,000. Further, individuals born with an OFC have higher infant mortality, higher mortality rates at all other stages of life, increased incidence of mental health problems, and higher risk for other disorders (notably including breast, brain, and colon cancers). Prior genome-wide linkage and association studies have now identified at least 18 genomic regions likely to contribute to the risk for nonsyndromic OFCs. Despite this substantial progress, the functional/pathogenic variants at OFC-associated regions are mostly still unknown. Because previous OFC genomic studies (genome-wide linkage, genome-wide association studies (GWAS), and targeted sequencing) are based on relatively sparse genotyping data, they cannot distinguish between causal variants and variants in linkage disequilibrium with unobserved causal variants. Moreover, it is unknown whether the association or linkage signals are due to single common variants, haplotypes of multiple common variants, clusters of multiple rare variants, or some combination. Finally, we cannot yet attribute specific genetic risk to individual cases and case families. Therefore, the goal of the current study is to identify specific OFC risk variants in Whites by performing whole genome sequencing of parent-case trios.

  Study phs001168

• Whole-Exome Sequencing and Targeted DNA Sequencing of Matched Ocular Melanocytosis and Uveal Melanoma

  Ocular melanocytosis is the most important predisposing condition for the eye cancer uveal melanoma (UM). Here we used whole-exome and deep targeted sequencing to identify for the first time a clonal Gq pathway mutation in ocular melanocytosis, which gave rise to UM. Additionally, we elucidated the order in which canonical genetic aberrations were acquired during tumor evolution. These findings provide a mechanistic explanation for the well-known clinical association of ocular melanocytosis with UM, and they provide new insights into UM tumor evolution. Reprinted from: Durante MA, Field MG, Sanchez MI, Covington KR, Decatur CL, Dubovy SR, Harbour JW. Genomic evolution of uveal melanoma arising in ocular melanocytosis, with permission from Cold Spring Harbor Molecular Case Studies.

  Study phs001835

• Direct genetic transformation bypasses tumor-associated DNA methylation alterations

  Tumors represent dynamically evolving populations of mutant cells, and many advances have been made in understanding the biology of their progression. However, key unresolved questions remain about the conditions that support their initial transformation, which cannot be easily captured in patient populations but are instead modeled using transgenic cellular or animal systems. Here, we used extensive patient atlas data to define common features of the tumor DNA methylation landscape as they compare to healthy human cells and used this benchmark to screen 21 engineered human and mouse models for their ability to reproduce these patterns. Notably, we find that genetically induced cellular transformation can trigger global changes in DNA methylation levels that are consistent with extensive proliferation but rarely recapitulate the widespread de novo methylation of Polycomb targets as found in clinical samples. Our results raise pertinent questions about the relationship between genetic and epigenetic aspects of tumorigenesis and provide an important molecular reference for evaluating existing as well as newer tumor models.

  Study EGAS50000000902

• NHLBI TOPMed: Genetic Epidemiology Network of Arteriopathy (GENOA)

  The Genetic Epidemiology Network of Arteriopathy (GENOA) is one of four networks in the NHLBI Family-Blood Pressure Program (FBPP). GENOA's long-term objective is to elucidate the genetics of target organ complications of hypertension, including both atherosclerotic and arteriolosclerotic complications involving the heart, brain, kidneys, and peripheral arteries. The longitudinal GENOA Study recruited European-American and African-American sibships with at least 2 individuals with clinically diagnosed essential hypertension before age 60 years. All other members of the sibship were invited to participate regardless of their hypertension status. Participants were diagnosed with hypertension if they had either 1) a previous clinical diagnosis of hypertension by a physician with current anti-hypertensive treatment, or 2) an average systolic blood pressure = 140 mm Hg or diastolic blood pressure = 90 mm Hg based on the second and third readings at the time of their clinic visit. Only participants of the African-American Cohort were sequenced through TOPMed. The Family Blood Pressure Program (FBPP), GENOA's parent program, is an unprecedented collaboration to identify genes influencing blood pressure (BP) levels, hypertension, and its target-organ damage. This program has conducted over 21,000 physical examinations, assembled a shared database of several hundred BP and hypertension-related phenotypic measurements, completed genome-wide linkage analyses for BP, hypertension, and hypertension associated risk factors and complications, and published over 130 manuscripts on program findings. The FBPP emerged from what was initially funded as four independent networks of investigators (HyperGEN, GenNet, SAPPHIRe and GENOA) competing to identify genetic determinants of hypertension in multiple ethnic groups. Realizing the greater likelihood of success through collaboration, the investigators created a single confederation with program-wide and network-specific goals. Comprehensive phenotypic data for GENOA study participants are available through dbGaP phs001238.

  Study phs001345

• What is metadata?

  What is metadata? Data represents units of information and metadata can be seen, simply put, as data about other data. For example, in a simple experiment in which a patient genome was sequenced, there are multiple and diverse fields of metadata: from the biological sex of the patient to the sequencing platform used. Another way to understand metadata, following our genomic experiment example, is going through the different layers of (meta)data: One of the basic units of information (data) would be the sequence of nucleotides (e.g. GCTGG and GCCGG). This DNA sequence can be contextualised within a chromosome by providing its locus (e.g. β-globin gene). This data, the locus, is about other data, the sequence of nucleotides, which would render it metadata. We can go one step further, and provide more context, by giving the associated phenotype of each of these sequences: GCTGG corresponds to a healthy individual, while GCCGG corresponds to a person with β-thalassaemia. Once again, this data is contextualising the data we have provided up to this point, which makes it metadata. With this simple example, what we are doing is adding layers of data that describe the ones below. Had we given the sequences alone, little would be possible from the researchers' point of view. But, now that the data has its accompanying metadata, a researcher could compare both sequences and their phenotypes to infer a possible cause of the disorder. Each layer of information broadens the possible applications of the data. Now that we know what metadata is, it is time to emphasise the importance of submitting good quality metadata. The quality of the metadata will determine whether the data is usable, discoverable, and interpretable by researchers and clinicians. One example that highlights the importance of good quality metadata is the description of biological sex of a patient: while the terms "female," "girl," or "woman" all represent the same concept, they are not harmonised. These different representations of a concept can create confusion and errors in data analysis. By applying standard definitions and terminologies to biological sex metadata, we can avoid misunderstandings and facilitate the integration of different datasets.  In order to comply with the FAIR principles and, more specifically, to allow for the (meta)data to be interoperable (i.e. used universally and unambiguously), we need to place some standards onto the (meta)data EGA  archives. These can be as simple as asserting that the given patient's biological sex is one of the correct terms (e.g. female or male); or as complex as multiple layers and combinations of validation steps with existing records. You can find further details on how EGA manages these standards on our metadata model page.

  Documentation submission/metadata/what-is-metadata

• Whole transcriptome sequencing datasets for Low-grade Serous Ovarian Carcinoma

  This dataset includes whole transcriptome sequencing reads from 8 cell lines based on TruSeq stranded mRNA kit (Illumina). They are all 2*75bp reads sequenced using Illumina NextSeq500.

  Dataset EGAD00001006441