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• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW20_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW20_C

  Dataset EGAD00001001796

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW22_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW22_C

  Dataset EGAD00001001799

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW2_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW2_M

  Dataset EGAD00001001813

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW32_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW32_C

  Dataset EGAD00001001814

• ENGAGE - Amendment "500 genes exon sequencing"

  The ENGAGE project is a FP7 funded EU project aiming to combine genetic and phenotype information from European population based cohorts. In this sub-project we aim to do whole exome sequencing of individuals selected from Health 2000 and FINRISK cohorts. Individuals have been selected based on their metabolic trait phenotypes

  Dataset EGAD00001000403

• IBD Whole Genome Sequencing (2019-08-14)

  Whole genome sequences at 15X depth of patients with Inflammatory Bowel Disease. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-08-14.

  Dataset EGAD00001005254

• Predictor_ChemoNEAR_TNBC (2019-08-14)

  In this study a collection of core biopsies from breast cancer patients receiving neoadjuvant chemotherapy as part of the ChemoNEAR trial will be investigated. The study is intended to detect early acquired resistance in women with diagnosed breast carcinoma. Samples will undergo whole genome sequencing and analysis, including use of HR Predict. . This dataset contains all the data available for this study on 2019-08-14.

  Dataset EGAD00001005255

• Whole genome sequencing

  The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC) is not well understood. We performed whole genome sequencing on primary and metastatic sites from highly clinically annotated HGSC samples. Samples were obtained pre-treatment based on a laparoscopic triage algorithm from patients who underwent R0 tumor debulking, or received neoadjuvant chemotherapy (NACT) with excellent or poor response.

  Dataset EGAD00001005240

• Sequencing files for "A Unifying Paradigm for Transcriptional Heterogeneity and Squamous Features in Pancreatic Ductal Adenocarcinoma."

  Files from DNA and RNA sequencing from primary tumors and metastases from pancreatic cancer patients along with matched normal tissues.

  Dataset EGAD00001005519

• RNA-sequencing

  RNA-sequencing for a cohort of B-ALL samples : 5 Down Syndrome (DS), 16 Hyperdiploid (HeH), 6 iAMP21, 9 other. RNA-sequencing for B-cell progenitors from 3 healthy. It also contains RNA-sequencing datasets of Patient-Derived Xenografts (X) developed from the B-ALL samples : 4 Down Syndrome (DS), 4 Hyperdiploid (HeH), 1 iAMP21, 3 other.

  Dataset EGAD00001005426

• H3Africa CAfGEN Exome

  Whole Exome Sequencing data from a retrospective paediatric HIV-disease progression cohort defined on the World Health Organization's criteria for paediatric HIV progression. Data comprises of BAM and VCF files for 314 participants from 2 countries: Botswana and Uganda. DNA and RNA samples are linked in bio-repository.

  Dataset EGAD00001006224

• Neoplastic pancreatic cysts and associated cancers

  Data from a study of 148 samples from IPMNs, MCNs, and small associated invasive carcinomas from 18 patients using whole exome or targeted sequencing. Sequencing data from 77 samples out of the 148 samples in the complete study are available in this dataset, based on the permissions given by the participating patients and the informed consents.

  Dataset EGAD00001006229

• Long read sequencing of 5 Intellectual Disability (ID) trios with PacBio Sequel. Dataset of samples: T2P, T2F and T2M

  5 trios were whole genome sequenced with PacBio Sequel to a depth of 15X (Trios 1-4) or 40X (Trio 5). For each trio the child was affected with severe ID, and the parents were unaffected. Dataset consists of Trio 2 samples: T2P, T2F and T2M

  Dataset EGAD00001006050

• Effect of the Placental Transcriptome on Stunting in a Longitudinal African Cohort

  Mammals with placentas and flowering plants evolved genomic imprinting in nutritive tissues, the placenta and endosperm, respectively. In these tissues, the genomes inherited from the mother and father are in conflict over resource allocation to offspring. In imprinted genes, transcription is repressed on the paternal or the maternal allele, resulting in allele specific expression (ASE). We investigated the variation in ASE of imprinted genes in term human placentas in order to detect loss of imprinting (LOI), which leads to partial expression of the repressed allele. We collected the placental tissue from birth to women in our multigenerational, prospective cohort study in Mali, West Africa. We followed the women from their own infancies, early childhood to adulthood (age 18+ years). Contingent on prior informed consent, we collected placental tissue and umbilical cord tissue. We conducted RNA-Seq of the fetal compartment of the placentas and targeted DNA-Seq of the umbilical cord tissue, which is fetal, and of saliva samples from parents. Our sequencing effort produced two datasets. The first dataset is the whole transcriptome RNA-Seq dataset of 111 biopsies (59 placentas) and genotyping of 96 genes. Birth length, weight, and placental weight for the children associated with this dataset are listed in the phenotype file (DOI: 10.1093/molbev/msz226). The second dataset includes targeted RNA-Seq of 262 samples (251 placentas) and targeted DNA-Seq for 766 genes. The genes were selected because they met any one of the following criteria: (1) imprinted and reported in some studies, (2) highly expressed in placenta, or (3) relevant to diseases of interest in this cohort (https://doi.org/10.1093/g3journal/jkab176). This study provides the first systematic analysis of variation in LOI across genes and individuals in a human population, and should shed light on the hypothesis that the modulation of imprinting is an epigenetic mechanism and plays a role in the regulation of offspring growth.

  Study phs001782

• Whole Exome Sequencing of Calcitonin Producing Pancreatic Neuroendocrine Neoplasms (CT-pNENs) Indicates a Unique Molecular Signature

  Calcitonin-producing pancreatic neuroendocrine neoplasms (CT-pNENs), which can mimic clinical and laboratory features of medullary thyroid carcinoma, are an extremely rare clinical entity with approximately 60 cases reported worldwide. The molecular profile of CT-pNENs is not yet known. Whole-exome sequencing (WES) was performed on tumor and corresponding serum samples of five patients with increased calcitonin serum levels and histologically proven calcitonin-positive CT-pNENs. cBioPortal analysis and gene enrichment analysis with DAVID were performed to validate candidate genes. Immunohistochemistry was used to detect protein expression of MUC4 and MUC16 in CT-pNEN specimens. Common somatic mutations of pNENs like MEN1, ATRX and PIK3CA were identified in cases of CT-pNENs. New somatic SNVs in ATP4A, HES4, and CAV3 have not yet been described in CT-pNENs. Pathogenic germline mutations in FGFR4 and DPYD were found in three of five cases. Mutations of CALCA (calcitonin) and the corresponding receptor CALCAR were found in all five tumor samples, but none of them resulted in clinical or protein sequelae. All five tumor cases showed single nucleotide variations (SNVs) in MUC4, and four cases showed SNVs in MUC16, both of which were membrane-bound mucins. Immunohistochemistry showed protein expression of MUC4 and MUC16 in one case each, and the liver metastasis of a third case was double positive for MUC4 and MUC16. The homologous recombination deficiency (HRD) score of all tumors was low.CT-pNENs have a unique molecular signature compared to other pNEN subtypes, specifically involving the FGFR4, DPYD, MUC4, MUC16 and the KRT family genes. However, these WES data from only five cases must be interpreted with caution because causal interpretation of the mutational landscape in CT-pNENs is difficult. Further research is needed to explain differences in pathogenesis compared with other pNENs. In particular, multi-omics data such as RNASeq, methylation, and whole genome sequencing could be informative.

  Study phs003060

• Metadata Public API

  Metadata Rest Endpoints Common Aspects Functionality Identifiers Requests and Responses Request Response Querying Querying by Object Cross-Querying by Object Common Aspects Functionality The Metadata REST API allows EGA users to request metadata from the EGA. Using this api you will be able to obtain the publicly available information from EGA study, sample, experiment, run, analysis, policy, dac and dataset. The API also allows for objects to be cross-referenced in order to obtain for example all the datasets linked to a dac. Identifiers EGA objects can be identified by their unique accession. These are ID's displayed everywhere, shared among all EGA locations and specific for each data type (More information on the list below) EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID Server Request and Response Request All the endpoints implement these two HTTP methods, GET and HEAD. Moreover, there is an authentication layer that allows to disclose the private information about each object if the user runs the endpoint with their token and has permissions to the related dataset. HTTP Method Description GET Returns the objects and their public information (including private information if the user has permissions) HEAD Returns the count of objects to be returned Response API responses are diverse but they always return a status call. Below you have a summary on what these codes mean and some tips that can help you troubleshooting them: HTTP Status Code Description Resolution 200 OK No error handling necessary 206 Partial Content Expected status code when paginating the results. No error handling necessary 400 BAD REQUEST Request incorrectly formulated 401 UNAUTHORISED/FORBIDDEN You do not have permissions over the object you are trying to access. / The authorised user is not permitted to make the given request. 404 NOT FOUND The object/resource you are trying to access does not exist. 500 INTERNAL SERVER ERROR This is a server-side error, try later. If the issue persists, contact the Heldpesk. Querying Querying by Object In the below documentation, worked examples can be found on how to use the API, to query about each unique EGA object. https://metadata.ega-archive.org/analyses/{id} https://metadata.ega-archive.org/dacs/{id} https://metadata.ega-archive.org/datasets/{id} https://metadata.ega-archive.org/runs/{id} https://metadata.ega-archive.org/samples/{id} https://metadata.ega-archive.org/studies/{id} Worked example for the EGA data access committee(DAC) EGAC00001000514 https://metadata.ega-archive.org/dacs/EGAC00001000514 Points to notice Please, be advised that all EGA objects can be queried by using the same endpoint. For example: https://metadata.ega-archive.org/datasets Returns all the datasets registered at the EGA. https://metadata.ega-archive.org/datasets?limit=5&offset=15 Returns 5 results skipping the initial 15 results. Cross-Querying by Object The EGA REST API Metadata also allows for the crossquerying of public metadata. For example, should I want to query the datasets included in the ICGC DAC: https://metadata.ega-archive.org/dacs/EGAC00001000010/datasets Below, you can find worked examples on how to perform the call to the API. https://metadata.ega-archive.org/datasets/EGAD00001000645/analyses https://metadata.ega-archive.org/datasetsEGAD00001000645/files https://metadata.ega-archive.org/datasets/EGAD00001000620/runs https://metadata.ega-archive.org/datasets/EGAD00001000620/samples https://metadata.ega-archive.org/samples/EGAN00001092114/datasets https://metadata.ega-archive.org/files/EGAF00000056146/dacs https://metadata.ega-archive.org/files/EGAF00000056146/datasets https://metadata.ega-archive.org/files/EGAF00000056146/studies There are more endpoints included in this category. Please, find all the possibilities (green tick) in the table below. Table The table displays in a ordered fashion the objects that can be crossreferenced using the metadata API. BY Analysis Dac Dataset Experiment Policy Run Sample Study File Analysis ✔ ✔ Dac ✔ ✔ Dataset ✔ ✔ ✔ ✔ Experiment ✔ ✔ ✔ ✔ Policy ✔ Run ✔ ✔ ✔ Sample ✔ ✔* ✔ Study ✔ ✔ ✔ ✔ ✔ ✔* File ✔ *: These cross queries do not include data from Array-File submissions. Check out the SPEC

  Documentation discovery/metadata/public-metadata-api

• RNA-Seq in Patients with Primordial Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in the interpretation of likely causal genetic variation through identification of altered transcript abundance and/or structure. RNA-Seq is the most sensitive assay for both investigating transcript structure and abundance The primary aim of this pilot project is to investigate to what degree integrating exome-Seq and RNA-Seq data on the same individual can accelerate the identification of causal alleles for rare genetic diseases. There are two main strands to this: (i) identifying which variants discovered in exome-seq appear to be having a functional impact on transcripts, and (ii) identifying transcript outliers, especially among known causal genes, that may not necessarily have a causal variant identified from exome sequencing. The latter may identify the presence of causal variants that lie far from coding regions (e.g. the formation of cryptic splice sites deep within introns, or loss of long range regulatory elements), which can be confirmed with further targeted genetic assays. Just over 50% of all disease-causing variants recorded in the Human Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g. nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs). This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients with primordial dwarfism syndromes, for 10 of these samples we have previously generate exome data as part of our collaboration with the group of Prof Andrew Jackson. The two remaining samples are positive controls where the causal mutation is known, and is known to affect transcript structure and/or abundance. Primordial dwarfism is a prime candidate for these RNA-seq studies because all known causal mutations to date have key roles in DNA replication and thus, unsurprisingly, the products of the causal genes are typically ubiquitously expressed. Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) per sample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity. 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 EGAD00001000640

• Integrated Epigenetic Maps of Human Embryonic, Extraembryonic and Adult Cells

  Working cooperatively with other Mapping Centers and the Data Coordination Center (EDACC) funded by this Roadmap mechanism we have comprehensively mapped the epigenomes of select human cells with significant relevance to complex human disease. Our effort has been focused on cells relevant to human health and complex disease including cells from the blood, brain, breast, skin, male germ cells, extraembryonic tissues and trophoblast, and U.S. Government-approved lines of human embryonic stem cells. We have incorporated high quality, homogeneous cells from males and females, and two predominant racial groups, and biological replicates of each cell type. The resulting comprehensive maps include up to 6 histone modifications selected for their opposing roles in regulating active and inactive chromatin (H3K4me1, H3K4me3, H3K9me3, H3K9ac, H3K27ac, H3K27me3, H3K36me3), DNA methylation, miRNA and gene expression, and for select cases whole genome shotgun sequence. Our cell and data production pipeline incorporates verification and data validation with independent methods, and operates under a model motivated by increased data production and decrease cost. Our group in conjunction with the other REMC teams, the EDACC, ENCODE, Epigenetics of Human Health and Disease centers and the NIH Roadmap program are developing methods, tools and reference epigenome maps for the research community that will make the promise of epigenetics in understand and treating human complex disease a reality. Our reference epigenomes will enable new disciplines including human population epigenetics, comparative epigenomics, neuroepigenetics, and therapeutic epigenetics for tissue regeneration and reversal of disease.

  Study phs000791

• NHLBI GO-ESP: Lung Cohorts Exome Sequencing Project (Lung Health Study of Chronic Obstructive Pulmonary Disease)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The Lung Health Study I was a randomized multicenter clinical trial with 5887 participants carried out from October 1986 to April 1994, designed to test the effectiveness of smoking cessation and bronchodilator administration in smokers aged 35 to 60 with mild lung function impairment. Participants were randomly assigned to one of three groups: usual care, who received no intervention smoking intervention with the inhaled bronchodilator ipratroprium bromide smoking intervention with an inhaled placebo The effect of intervention was evaluated by the rate of decline of forced expiratory volume in one second (FEV1).

  Study phs000291

• RNA-Sequencing of B-Lymphoblastic Leukemia with Glucocorticoids and PI3K Delta Inhibition

  Mononuclear cells were isolated from bone marrow or peripheral blood of 7 pediatric subjects with B-lymphoblastic leukemia at the time of diagnosis. To determine the effect of PI3K delta inhibition on glucocorticoid-induced gene regulation, B-lymphoblastic leukemia cells were treated with glucocorticoids +/- the PI3K delta inhibitor, idelalisib, for 24 hours prior to RNA extraction and sequencing. Biological replicates were performed for 4 of the 7 subjects; 2 of these subjects had specimens demonstrating an additive response to the combination of glucocorticoids and idelalisib in viability testing in vitro, and 2 subjects' specimens demonstrated a synergistic response. All 7 subjects were analyzed together and the 4 specimens with biological replicates were also evaluated in an additional analysis. An average of 40 million reads per specimen and treatment condition were obtained. We compared gene expression in each treatment condition to vehicle-treated cells and expression in glucocorticoid or idelalisib only treated cells to combination treated cells. Using a high dose of dexamethasone (25 or 50 nM) and an equivalent dose of prednisolone, we found that the addition of idelalisib (500 nM) enhanced prednisolone-induced gene regulation but not dexamethasone-induced gene regulation. Surprisingly, the specimens with additive response to combination therapy demonstrated enhancement of prednisolone-induced gene regulation with the addition of idelalisib, while the specimens with synergistic responses did not. Raw sequencing data (FASTQ) and count tables will be available through dbGaP.

  Study phs003085

• Michigan Polybrominated Biphenyl (PBB) Exposure Registry

  Humans are exposed to chemicals such as brominated flame retardants (BFRs) at unprecedented levels, and a wide variety of health effects are attributed to such exposures. However, the biological mechanisms that link exposures to its consequences remain unknown. An industrial accident in the 1970's exposed over 4000 individuals in rural Michigan to polybrominated biphenyl (PBB), a BFR that was present in the food supply for years prior to detection and management. Health effects are still evident in these individuals and their children. Because this population has been assessed regularly since the exposure, it is an ideal group in which to examine the molecular mechanisms that contribute to susceptibility, vulnerability and health effects. The goal of this project is to identify the genetic variants that associate with the rate of PBB elimination over time and integrate genetic and epigenetic datasets and identify complex gene-environment relationships in PBB exposed individuals. We will leverage data generated as part of past and ongoing studies in the Michigan Polybrominated Biphenyl Registry. We anticipate that this study will provide insight into how genetic variants and the environment interact in relation to PBB exposure and its health effects. We also anticipate the results of this study will be informative for studies of BFRs and other endocrine disrupting compounds with similar chemical properties. Note that methylation array data is available from NCBI GEO under GSE116339: Exposure to Polybrominated Biphenyl (PBB) Associates with DNA Methylation Differences Across the Genome

  Study phs001862

• Systems genetics in human endothelial cells identifies non-coding variants modifying enhancers, expression, and complex disease traits

  Identification of causal variants and mechanisms underlying complex disease traits in humans requires strategies to locate and fine-map functional regulatory variants in disease-relevant cell types. To discover functional regulatory variants in primary aortic endothelial cells (ECs) from humans, we collected genetic, transcriptomic, and four epigenomic phenotypes in a population of 153 human donors representing individuals of both sexes and three major ancestries. We found thousands of EC eQTLs that were not present in GTEx at all ranges of effect sizes, indicating novel functional variants not observable from tissue data. We performed several epigenetic assays across 53 donors' EC to enable molecular QTL mapping, which included chromatin accessibility, histone modification, and transcription factor binding of proteins ERG and NF-kB/p65 in two activation states. We discovered over 3000 regulatory elements where cis-regulatory variants associated to significant differences in epigenetic marks. Co-localization with our eQTLs, TF motif mutations, and 3D confirmation capture data in ECs enabled our discovery of hundreds of high-confidence functional regulatory elements that perturb endothelial molecular phenotypes. Furthermore, this set of variants is enriched at GWAS loci for Coronary Artery disease and other disease traits, with some SNPs demonstrating pleiotropic effects. Together, our dataset and analytical approach provide the genetics and vascular biology communities with specific variants affecting EC biology and serves as a proof-of-principle for how to detect functional regulatory variants in human cells with relevance to complex traits.

  Study phs002057

• Cellular Indexing of Transcriptomes and Epitopes Sequencing (CITE-Seq) Analysis to Investigate the Impact of Granulocyte-Colony Stimulating Factor on CRISPR/Cas9 Gene Edited Human Hematopoietic Stem Cell Function

  Our research using in-vivo preclinical xenograft mouse models demonstrated that G-CSF impedes engraftment of CRISPR-Cas9 gene edited human hematopoietic stem cells (HSCs). In this CITE-seq study, we sought to investigate the mechanisms by which G-CSF negatively impacts long-term repopulating functions of CRISPR-Cas9 gene edited human HSCs. Accordingly, human CD34+ cells were obtained from a healthy volunteer and edited with Cas9 alone (Cas9 group), Cas9+AAVS1-targeting gRNA (RNP group), or Cas9+AAVS1-targeting gRNA+GSE56 (RNP/GSE56 group). Then, these edited cells were transplanted into busulfan-conditioned NSG mice, and these mice subsequently received 3 days of phosphate buffered saline (PBS) or G-CSF. Each mouse was subsequently euthanized and harvested for bone marrow cells and human CD34+cells were isolated using immunomagnetic beads. Isolated CD34+ cells from a total of 6 mice were individually stained with Total seq B CITE-seq antibodies (CD38, CD45RA, CD90, CD49f) + hashtag oligo antibodies 1, 2, 3, 4, 5 and 6. Fluorescence activated cell sorting (FACS) was used to purify ~2,500 cells from each group that were subsequently pooled for CITE-seq library preparation and sequencing. Seurat was used to demultiplex data into 6 individual groups and differential gene expression analysis was performed to evaluate the impact of G-CSF within Cas9, RNP and RNP/GSE56 groups.

  Study phs003277

• Pediatric Investigation for Genetic Factors Linked with Renal Progression (PediGFR)

  The Pediatric Investigation for Genetic Factors Associated with Renal Progression (PediGFR) (RO1-DK082394) is an international collaborative study among three large prospective cohort studies of children with chronic kidney disease. The participating parent cohort studies are the Chronic Kidney Disease in Children (CKiD), the Effect of Strict Blood Pressure Control and ACE Inhibition on CRF Progression in Pediatric Patients (ESCAPE), and the Cardiovascular Comorbidity in Children with Chronic Kidney Disease (4C) study. In these cohorts, pediatric subjects with CKD have been prospectively followed with standardized measurements for renal progression. The dbGaP data upload will utilize the structure of sub-studies to include the genotype and baseline phenotype for the three cohorts, as well as the RBC trait and anemia data for a sub-study under PI Susan Furth: Role of Genetic Variation in the Anemia of Chronic Kidney Disease (K24DK078737). In brief PediGFR is a prospective study of children with chronic kidney disease (CKD) to determine genetic factors associated with kidney function measured by the estimated glomerular filtration rate (eGFR) by Schwartz equation. The PediGFR_v2 Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000842 PediGFR_v2 Cohort. phs000843 4C phs000650 CKiD phs000844 ESCAPE

  Study phs000842

• International Consortium on the Genetics of Systemic Lupus Erythematosus (SLEGEN)

  The genetic makeup of an individual strongly influences the risk of developing systemic lupus erythematosus (SLE). The identification of genes that predispose an individual to SLE will lead to earlier and better diagnosis, better treatments, and possibly prevention. To this end, the International Consortium on the Genetics of Systemic Lupus Erythematosus (SLEGEN) was formed in 2005 and is composed of lupus researchers who agreed to pool their knowledge and resources to search for genes that predispose to lupus. Eight laboratories contributed DNA samples for genotyping at the Broad Institute and association with SLE was performed by the Data Coordinating Center (Wake Forest University), as part of a four stage study design. Stages one and two of this design were graciously funded by the Alliance for Lupus Research (www.lupusresearch.org). In this stage of the study, approximately 767 SLE patients (cases) were compared to approximately 383 non-SLE patients (controls) for differences among the Illumina HumanHap300. The affected individuals are all females of European decent. 82% of the cases are the index case from multiplex pedigrees for SLE and the remaining 18% have self-reported first degree relatives with SLE. A detailed summary of the methods and results can be found in the manuscript in Nature Genetics February 2008 by SLEGEN "Genome-wide association scan in women with systemic lupus erythematosus identifies susceptibility variants ITGAM, PXK, KIAA1542 and other loci". (Please see also Study Accession: phs000202.v1.p1)

  Study phs000216

• Deletion of FUNDC2 and CMC4 on chromosome Xq28 is sufficient to cause hypergonadotropic hypogonadism in men

  Hypergonadotropic hypogonadism (HH) is characterized by low sex steroid levels and secondarily elevated gonadotropin levels with either congenital or acquired etiology. Genetic factors leading to HH have yet to be fully elucidated. We submit genome and transcriptome data analyses from a male patient with HH and history of growth delay who has an inherited deletion of chromosome Xq28. Expression analyses were done for this patient and his unaffected family members, and compared to normal controls to identify dysregulated genes due to this deletion. Our patient's Xq28 deletion is 44,806 bp and contains only two genes, FUNDC2 and CMC4. Expressions of both FUNDC2 and CMC4 are completely abolished in the patient. Gene ontology analyses of differentially expressed genes in the patient in comparison to controls show that significantly up-regulated genes in the patient are enriched in Sertoli cell barrier regulation, apoptosis, inflammatory response and gonadotropin-releasing regulation. Indeed, our patient has an elevated FSH level, which regulates Sertoli cell proliferation and spermatogenesis. In his mother and sister, who are heterozygous for this deletion, X-chromosome inactivation is skewed towards the deleted X, suggesting a mechanism to avoid FSH dysregulation. Compared to the previously reported men with variable sized Xq28 deletions, our study suggests that the loss of function of FUNDC2 and/or CMC4 results in dysregulation of apoptosis, inflammation and FSH, and is sufficient to cause Xq28-associated HH.

  Study phs002234

• Genome Wide Association for Asthma and Lung Function

  The SNP Typing for Association with Multiple Phenotypes from Existing Epidemiologic (STAMPEED) asthma project includes subjects with asthma and controls from the Chicago Asthma Genetics Study (CAG), NHLBI multicenter Severe Asthma Research Program (SARP) and NHLBI Collaborative Studies on the Genetics of Asthma CSGA (Wake Forest). All studies included European American and African American children and adults with asthma ranging from mild to severe and adult controls. CAG participants were collected at the University of Chicago. SARP participants were recruited at the NHLBI SARP sites with an emphasis on recruiting severe asthmatics (Moore et al, Am J Respir Crit Care Med, 2010, PMID: 19892860). CSGA cases and controls collected by the Wake Forest investigators were also included. Asthma status was based on both a physician's diagnosis and either bronchodilator reversibility or hyper-responsiveness to methacholine as well as less than 5 pack years of smoking. Genotyping was performed on the Illumina 1Mv1 platform, with individual genotypes called using clustering algorithms as implemented in the BeadStudio software by Illumina. The total number of markers following standard QC was 1,025,129. Imputation was performed using the HapMap phase 2, release 21 SNPs using MACH with the phased HapMap CEU and YRI haplotypes as a reference. Case/control association tests for asthma status were performed using logistic regression in R (http://CRAN.R-project.org/) on genotype dosages, and adjusting for the first principal component from EIGENSTRAT.

  Study phs000355

• Whole Exome Sequencing of DNA from Pre-and Post-Chemotherapy Needle Biopsies of Triple Negative and Inflammatory Breast Cancers Enrolled in the S0800 Trial

  Purpose: The purpose of this study was to assess the somatic mutation landscape of breast tumors before and after neoadjuvant chemotherapy. The data includes whole exome sequencing of pre- and post- tissues that were collected in the context of an already published clinical trial SWOG S0800 (ZA Nahleh et al. Breast Cancer Research and Treatment. 158:485-495, 2016). The trial compared the efficacy of sequential nab-paclitaxel followed or preceded by doxorubicin/cyclophosphamide anthracycline chemotherapy with or without bevacizumab as preoperative therapy for stage II-III breast cancer. Experimental Design: 29 pre-treatment biopsies and 9 matching post-treatment surgically resected cancer tissues were available for analysis and were subjected to whole exome sequencing to identify mutational patterns associated with response to neoadjuvant chemotherapy. The 9 paired samples with residual invasive cancer after therapy were also analyzed to assess changes in mutational patterns in response to therapy. No matching normal tissues were available for germline sequencing and therefore we used n=7 post-treatment breast tissues without residual cancer (i.e. complete eradication of cancer by therapy) as a normal cohort to facilitate somatic variant calling.Conclusion: These results suggest that genomic disturbances in BRCA-related DNA repair mechanisms, reflected by a dominant mutational signature 3, confer increased chemotherapy sensitivity. Cancers that survive neoadjuvant chemotherapy, frequently have alterations in cell cycle regulating genes but different genes are affected in different patients.

  Study phs001883

• University of Texas PDX Development and Trial Center Grant

  The goal for the University Texas PDX Development and Trial Center (UTPDTC) is to optimize personalized biomarker-based cancer therapy and identify effective targeted drugs based on the molecular characteristics of each tumor. Our short-term goals are to establish a biobank of clinically, and molecularly-annotated Patient-Derived Xenografts (PDXs) and to use PDXs as a platform for preclinical drug development and biomarker discovery. The primary goal for UTPDTC investigators will be to develop PDX trial strategies for preclinical testing of single agents and drug combinations. These models will allow the determination of the optimal treatments (single drugs or combinations) that should be tested in clinical trials in increasingly individualized, molecularly defined subsets of tumors. The goal of the Patient-Derived Xenograft Core is to provide high-quality clinically relevant and molecularly annotated PDX models for the research projects proposed in the University of Texas PDX Development and Trial Center (UTPDTC) grant application and to the research activity of the NCI PDX Development and Trial Centers Research Network (PDXNet) by leveraging PDX resources at our institutions and developing new PDX models from human cancer specimens using rigorous quality standards so that the models can be used to guide clinical trial development. The PDX models developed and/or characterized by the PDX Core will be available to other cancer researchers through the PDXNet and NCI Patient-Derived Models Repository (PDMR).

  Study phs001980

• MAP Kinase-Mutant Hematologic Malignancies and Their Therapeutic Resistance

  The Mitogen-Activated Protein Kinase (MAPK) signaling pathway has been critically important in understanding pathology and developing targeted therapy for many cancers, but high frequency mutations in this pathway in hematopoietic malignancies were unknown until a series of sequencing studies from our group and others revealed a high frequency of activating mutations in BRAF (GeneID:673), MAP2K1 (GeneID:5604), and other key components of the MAPK pathway in two groups of rare and poorly studied blood cancers: hairy cell leukemia (HCL) and the systemic histiocytoses (SH). Although HCL and the SH both share common gene mutations in BRAF (BRAFV600E) and MAP2K1, these are distinct blood cancers with different clinical behaviors; however, their actual developmental cellular origins, genomic, and pathogenic differences are poorly understood, which led to our project goal of determining how BRAFV600E, MAP2K1, and other MAPK pathway mutations contribute to the pathogenesis of distinct blood cancers and affect their clinical responses to MAPK pathway inhibitors. This study proposal seeks to advance our understanding of the actual cells of origin of cancer-causing MAPK mutations in HCL and the SH, to determine why BRAFV600E and MAP2K1 mutations can cause two distinct blood cancers, and to understand how these mutations in HCL and SH influence responses to MAPK pathway inhibitor drugs and other receptor tyrosine kinase (RTK) inhibitors such as RET and ALK inhibitors that could potentially become effective therapy for these poorly understood blood cancers.

  Study phs001864

• Use of Whole Genome Sequencing for Diagnosis and Discovery in the Cancer Genetics Clinic

  Despite the potential of whole-genome sequencing (WGS) to improve patient diagnosis and care, the empirical value of WGS in the cancer genetics clinic is unknown. We performed WGS on members of two cohorts of cancer genetics patients: those with BRCA1/2 mutations (n = 176) and those without (n = 82). Initial analysis of potentially pathogenic variants (PPVs, defined as nonsynonymous variants with allele frequency < 1% in ESP6500) in 163 clinically-relevant genes suggested that WGS will provide useful clinical results. This is despite the fact that a majority of PPVs were novel missense variants likely to be classified as variants of unknown significance (VUS). Furthermore, previously reported pathogenic missense variants did not always associate with their predicted diseases in our patients. This suggests that the clinical use of WGS will require large-scale efforts to consolidate WGS and patient data to improve accuracy of interpretation of rare variants. While loss-of-function (LoF) variants represented only a small fraction of PPVs, WGS identified additional cancer risk LoF PPVs in patients with known BRCA1/2 mutations and led to cancer risk diagnoses in 21% of non-BRCA cancer genetics patients after expanding our analysis to 3209 ClinVar genes. These data illustrate how WGS can be used to improve our ability to discover patients' cancer genetic risks. "Reprinted from doi:10.1016/j.ebiom.2014.12.003, with permission from EBioMedicine."

  Study phs000942

• MILK-Omics: Systems Biology of Human Milk and Its Links to Maternal and Infant Health

  The primary objective of the project is to generate a systems-level view of human milk in the context of healthy mothers and their term infants. The study uses biospecimens and clinical data from the Mothers and Infants LinKed for Healthy Growth Study (MILk Study), a prospective observational cohort of approximately 500 exclusively breastfeeding women and their infants who are followed to 6 months of age. The project focuses on mature milk samples collected at 1 month postpartum and infant gut microbiome samples collected at 1 and 6 months of age. Specific Aim 1 is to identify maternal genetic and clinical factors that shape human milk gene expression. Using bulk and single-cell RNA sequencing of the milk cell pellet and genotypes from maternal DNA, we will identify novel genetic determinants of the milk transcriptome and assess potential modification of these genetic associations by gestational weight gain, diet, and other clinical factors. Specific Aim 2 is to describe key features of the normative human milk biosystem and their interactions with one another. Specifically, machine learning techniques will be used to characterize interaction networks and correlational structures among the following features of human milk: transcriptomics, microbiomes, oligosaccharides, metabolomics, lipidomics, and milk macronutrient composition. Specific Aim 3 is to establish how the milk biosystem is related to variation in infant gut microbiomes and health. dbGaP will house the maternal genotype and milk transcriptomics data.The infant microbiome sequence data are associated with BioProject PRJNA1019702.

  Study phs003408

• Trisomy 21 Dosage Compensation Map (T21DoCoMap)

  Excess gene dosage from human chromosome 21 (HSA21), due to trisomy or translocation of HSA21 material, causes Down syndrome (DS). We derived trisomy 21 (T21) induced pluripotent stem cells (iPSCs) alongside otherwise isogenic euploid controls from mosaic DS fibroblasts (GM00260, first described in Lubiniecki et al., PMID: 225951) of the NIGMS genetic cell repository, to enable analysis of whole-chromosomal and individual gene dosage imbalance in the context of in vitro models of DS development. Virtual karyotyping (by Infinium CytoSNP-850k), and phased genotyping (by linked-read whole-genome sequencing) of the resulting iPSC lines provide a deeply-characterized genomic platform for dissection of HSA21 gene dosage. We apply this highly unique resource to allelic analysis of mRNA sequencing of iPSCs and differentiated neural lineages, and demonstrate its utility in the context of inducible HSA21 dosage compensation. To this end, we equipped one distinct HSA21 copy with a doxycycline-inducible XIST transgene, which endogenously silences one X in 46,XX females. Standard and allele-specific RNA-seq analysis confirms mono-allelic T21 silencing to be virtually complete and irreversible, further supported by DNA methylation data (Infinium methylEPIC). This full-length HSA21 map of phased single-nucleotide and insertion/deletion variants enables allele-specific applications for gene-level dissection T21 dosage effects. Because our XIST remains inducible in post-mitotic T21 neurons and astrocytes, we perform single-nuclei RNA-seq to demonstrate XIST efficiently represses genes even after terminal differentiation.

  Study phs002397

• CRISPR screening in human trophoblast stem cells reveals both shared and distinct aspects of human and mouse placental development

  The placenta serves as the interface between the mother and fetus, facilitating the exchange of gases and nutrients between their separate blood circulation systems. Trophoblasts in the placenta play a central role in this process. Our current understanding of mammalian trophoblast development relies largely on mouse models. However, given the diversification of mammalian placentas, findings from the mouse placenta cannot be readily extrapolated to other mammalian species, including humans. To fill this knowledge gap, we performed CRISPR knockout (KO) screening in human trophoblast stem cells (hTSCs). We targeted genes essential for mouse placental development and identified more than 100 genes as critical regulators in both human hTSCs and mouse placentas. Among them, we further characterized in detail two transcription factors, DLX3 and GCM1, and revealed their essential roles in hTSC differentiation. Moreover, a gene function-based comparison between human and mouse trophoblast subtypes suggests that their relationship may differ significantly from previous assumptions based on tissue localization or cellular function. Notably, our data reveal that hTSCs may not be analogous to mouse TSCs or the extraembryonic ectoderm (ExE) in which in vivo TSCs reside. Instead, hTSCs may be analogous to progenitor cells in the mouse ectoplacental cone and chorion. This finding is consistent with the absence of ExE-like structures during human placental development. Our data not only deepen our understanding of human trophoblast development but also facilitate cross-species comparison of mammalian placentas.

  Study JGAS000659

• Genomic landscapes of endometrioid and mucinous ovarian cancers and morphologically similar tumor types

  While endometrioid and mucinous ovarian cancers represent nearly a quarter of ovarian cancers, their molecular characteristics and pathologic origins are poorly understood. To characterize the genomic and epigenomic alterations of these ovarian cancer subtypes and evaluate links to morphologically similar tumors from other sites, we performed sequence, copy number, mutation signature, rearrangement, and methylation analyses from tumor samples and matched normal tissues of 133 patients. These analyses included patients with ovarian endometrioid (n=44), ovarian mucinous (n=43), uterine endometrial (n=15), and gastrointestinal mucinous cancers (n=31). In addition to identifying genes previously known to be involved in these tumors, we identified alterations in RAD51C, NOTCH4, SMARCA1/4 and JAK1 in ovarian endometrioid, ESR1 in uterine endometrioid, and SMARCA4 in ovarian mucinous cancers. Whole genome sequencing revealed rearrangements involving PTEN, NF1, and NF2 in ovarian endometrioid tumors, and NF1 and MED1 in ovarian mucinous cancers. The number of alterations and affected genes in ovarian and uterine endometrioid cancers were similar as were genome-wide methylation profiles, suggesting that these tumors may have a similar tissue of origin. By contrast, methylation patterns in ovarian mucinous cancers were more similar to other gastrointestinal mucinous cancers, including mucinous cancers of the stomach, colon, and pancreas. These analyses provide insights into the genomic landscapes and origins of mucinous and endometrioid ovarian carcinomas, providing new avenues for early clinical intervention and management of patients with these cancers.

  Study EGAS50000000523

• The patterns and dynamics of genomic instability in metastatic pancreatic cancer

  Pancreatic cancer is an aggressive malignancy with a five-year mortality of 97–98%, usually due to widespread metastatic disease. Previous studies indicate that this disease has a complex genomic landscape, with frequent copy number changes and point mutations, but genomic rearrangements have not been characterized in detail. Despite the clinical importance of metastasis, there remain fundamental questions about the clonal structures of metastatic tumours, including phylogenetic relationships among metastases, the scale of ongoing parallel evolution in metastatic and primary sites, and how the tumour disseminates. Here we harness advances in DNA sequencing to annotate genomic rearrangements in 13 patients with pancreatic cancer and explore clonal relationships among metastases. We find that pancreatic cancer acquires rearrangements indicative of telomere dysfunction and abnormal cell-cycle control, namely dysregulated G1-to-S-phase transition with intact G2–M checkpoint. These initiate amplification of cancer genes and occur predominantly in early cancer development rather than the later stages of the disease. Genomic instability frequently persists after cancer dissemination, resulting in ongoing, parallel and even convergent evolution among different metastases. We find evidence that there is genetic heterogeneity among metastasis-initiating cells, that seeding metastasis may require driver mutations beyond those required for primary tumours, and that phylogenetic trees across metastases show organ-specific branches. These data attest to the richness of genetic variation in cancer, brought about by the tandem forces of genomic instability and evolutionary selection.

  Study EGAS00000000064

• Cancer-associated fibroblasts promote drug resistance in ALK-driven lung adenocarcinoma cells by upregulating lipid biosynthesis

  Targeted therapy interventions using tyrosine kinase inhibitors (TKIs) provide encouraging treatment responses in ALK-rearranged lung adenocarcinomas, yet resistances occur almost inevitably. Apart from tumor cell-intrinsic resistance mechanisms, accumulating evidence supports a role of cancer-associated fibroblasts (CAFs) in affecting the therapeutic vulnerability of lung cancer cells. Here, we aimed to investigate underlying molecular networks shaping the therapeutic susceptibility of ALK-driven lung adenocarcinoma cells via tumor microenvironmental cues using three-dimensional (3D) spheroid co-culture settings. We show that CAFs promote therapy resistance of lung tumor cells against ALK inhibition by reducing apoptotic cell death and increasing cell proliferation. Using single-cell RNA-sequencing analysis, we show that genes involved in lipogenesis constitute the major transcriptional difference between TKI-treated homo- and heterotypic lung tumor spheroids. CAF-conditioned medium and CAF-secreted factors HGF and NRG1 were both able to promote resistance of 3D-cultured ALK-rearranged lung tumor cells via AKT signaling, which was accompanied by enhanced de novo lipogenesis and supression of lipid peroxidation. Notably, simultaneous targeting of ALK and SREBP-1 was able to overcome the established CAF-driven lipid metabolic-supportive niche of TKI-resistant lung tumor spheroids. Our findings highlight a crucial role of CAFs in mediating ALK-TKI resistance via lipid metabolic reprogramming and suggest new ways to overcome resistance towards molecular directed drugs by targeting vulnerabilities downstream of oncogenic signaling.

  Study EGAS50000000135

• Decoding Human Endogenous Retrovirus Expression in Liver Metastatic Colorectal Cancers: Implications for Diagnosis and Prognosis

  The association between Human Endogenous RetroVirus (HERV) expression and cancer can be considered to both reflect the epigenetic deregulation of cancer and facilitate oncogenesis through its promoter/enhancer action on genes. More than 50% of colorectal cancers develop liver metastases and HERV has never been studied in this setting. We collected 400 RNAseq samples from more than 200 patients with primary and liver metastases from published and unpublished databases. We corroborated our findings with tandem mass spectrometry from primary colorectal cancer and single-cell RNAseq from liver metastatic colorectal cancer (lmCRC). We identified global stability in HERV expression between liver metastases and primary colorectal cancers, suggesting an early oncogenic footprint. Therefore, we proposed a list of seventeen HERV loci for lmCRC characterization with ERV-derived peptides but no expression in normal tissues. Among them, we discovered six prognostic markers after surgical resection of lmCRC. Four of them, HERVH_Xp22.32a, HERVH_20p11.23b, HERVH_13q33.3, HERVH_13q31.3, showed poor prognostic value when expressed (log-rank p-value 0.028, 0.0083, 9e-4, 0.05, respectively). HERVH_Xp22.2c (log-rank p-value 0.032) and HERVH_8q21.3b (only in multivariate models) were associated with better prognosis when expressed. These markers showed a cumulative effect on survival when expressed. Some HERVs were associated with decreased cytotoxic immune cells and most of them correlated with cell cycle pathways. Our findings provide new insights into lmCRC classification and suggest novel prognostic biomarkers and potential therapeutic targets.

  Study EGAS50000000307

• Systematic Growth Factor Profiling Platform for 3D Tumor Models Reveals EstradiolResponsive Cellular Mechanisms of Immunotherapy Resistance

  Epithelial ovarian cancer (EOC) exhibits significant molecular heterogeneity, which is thought to be influenced by the tumor microenvironment (TME). However, the specific factors driving this heterogeneity remain poorly understood. In this study, we integrated growth factoromics and genomic data to identify TME factors contributing to EOC heterogeneity and immunosuppression. Our analysis revealed distinct subgroups of EOC samples with differential responsiveness to specific growth factors, particularly estradiol and R-spondin. Notably, samples with high responsiveness to estradiol and Wnt (C1 cluster) were enriched in the Mesenchymal (MES) molecular subtype, while samples with high responsiveness to R-spondin (C2 cluster) were associated with the Differentiated (DIF) and Immunoreactive (IMR) subtypes. We discovered that the G protein-coupled estrogen receptor (GPER), rather than the classical estrogen receptor alpha (ERα), was the key mediator of estrogen responsiveness and a determinant of molecular subtype classification. Single-cell sequencing analysis identified subsets of estrogen-responsive malignant cell (MAL.PDCD5) and cancer-associated fibroblast (FB.TNFSF10), which were associated with immunosuppressive patterns in the TCGA cohort. Importantly, the interaction between these cell populations significantly increased upon estrogen treatment, suggesting a potential mechanism by which estrogen signaling may contribute to the development of an immunosuppressive TME. Our findings highlight the critical role of estrogen signaling in shaping the molecular heterogeneity and immunosuppressive TME of EOC and provide novel insights into potential therapeutic targets for overcoming immunosuppression in this malignancy.

  Study EGAS50000000422

• Tumor-reactive heterotypic CD8 T cell clusters from clinical samples

  Emerging evidence suggests a correlation between CD8+ T cell-tumor cell proximity and anti-tumor immune response. However, it remains unknown whether these cells exist as functional clusters that can be isolated from clinical samples. By conventional and imaging flow cytometry, we show here that from 21/21 human melanoma metastases, we could isolate heterotypic clusters, comprising CD8+ T cells interacting with one or more tumor cells and/or antigen-presenting cells (APCs). Single-cell RNA-sequencing revealed that T cells from clusters were enriched for gene signatures associated with tumor reactivity and exhaustion. Clustered T cells exhibited increased TCR clonality indicative of expansion, while TCR-matched T cells showed more exhaustion and co-modulation when conjugated to APCs than to tumor cells. T cells that were expanded from clusters ex vivo exerted on average 9-fold increased killing activity towards autologous melanomas, which was accompanied by enhanced cytokine production. Upon adoptive cell transfer into mice, T cells from clusters showed improved patient-derived melanoma control, which was associated with increased T cell infiltration and activation. Together, these results demonstrate that tumor-reactive CD8+ T cells are enriched in functional clusters with tumor cells and/or APCs and that they can be isolated and expanded from clinical samples. Typically excluded by single cell gating in flow cytometry, these distinct heterotypic T cell clusters serve as a valuable source to decipher functional tumor-immune cell interactions, while they may also be therapeutically explored.

  Study EGAS50000000785

• Pseudodiastrophic dysplasia expands the known phenotypic spectrum of defects in proteoglycan biosynthesis

  Pseudodiastrophic dysplasia (PDD) is a severe skeletal dysplasia associated with prenatal manifestation and early lethality. Clinically, PDD is classified as a ‘dysplasia with multiple joint dislocations’ however, the molecular aetiology of the disorder is currently unknown. In order to identify the genetic defects underlying PDD, we performed whole exome sequencing (WES) on 3 patients from 2 unrelated families, clinically diagnosed with PDD. WES resulted in the identification of bi-allelic variants in the established skeletal dysplasia genes, B3GAT3 (Family 1) and CANT1 (Family 2). Mutations in these genes have previously been reported to cause ‘multiple joint dislocations, short stature, and craniofacial dysmorphism with or without congenital heart defects’ (B3GAT3) and Desbuquois dysplasia 1 (CANT1); disorders in the same nosological group as PDD. Follow-up of the B3GAT3 variants demonstrated significantly reduced B3GAT3/GlcAT-I expression. Downstream in vitro functional analysis revealed abolished biosynthesis of glycosaminoglycan side chains on proteoglycans. Functional evaluation of the CANT1 variant showed impaired nucleotidase activity, which results in inhibition of glycosaminoglycan synthesis through accumulation of uridine diphosphate. For the families described in this study, the PDD phenotype was caused by mutations in the known skeletal dysplasia genes B3GAT3 and CANT1, demonstrating the advantage of genomic analyses in delineating the molecular diagnosis of skeletal dysplasias. This finding expands the phenotypic spectrum of B3GAT3- and CANT1- related skeletal dysplasias to include PDD, and highlights the significant phenotypic overlap of conditions within the proteoglycan biosynthesis pathway.

  Study EGAS00001004145

• Evolutionary origin and methylation status of human intronic CpG islands that are not present in mouse

  Imprinting of the human RB1 gene is due to the presence of a differentially methylated CpG island (CGI) in intron 2, which is part of a retrogene derived from the PPP1R26 gene on chromosome 9. The murine Rb1 gene does not have this retrogene and is not imprinted. We have investigated whether the RB1/Rb1 locus is unique with respect to these differences. For this we have compared the CGIs from human and mouse by in silico analyses and found out that there are at least 2033 human intronic CGIs that are not present in the mouse. Among these CGIs, 104 show sequences similarities elsewhere in the human genome, which suggests that they arose by retrotransposition. We could narrow down the time points when most of these CGIs appeared during evolution. Their methylation status was analysed in two monocyte methylome datasets from whole genome bisulfite sequencing and in 18 published methylomes. Five CGIs appear to be differentially methylated, which suggests that they are subject of genomic imprinting. They are located in introns of the following genes: RB1, ASRGL1, PARP11, PDXDC1 and MYO1D. Four of these CGIs are parts of retrogenes. Our study supports the notion that imprinting builds on host defence mechanisms by which the genome protects itself against retrotransposed and foreign DNA and that the epigenetic fate of the retrotransposed DNA depends on selective forces at the integration site.

  Study EGAS00001000719

• Germline variants collaborate with somatic mutations and initiate and/or drive disease in primary myelodysplastic syndrome (MDS) and therapy-related myeloid neoplasms (t-MN)

  Therapy-related myeloid neoplasms (T-MN) are poorly characterized secondary hematological malignancies following chemotherapy/radiotherapy exposure. We compared the clinical and mutational characteristics of T-MN (n=129) and primary myelodysplastic syndrome (P-MDS, n=108) patients. Although the somatic mutation frequency was similar between T-MN and P-MDS patients (93% in both groups), the pattern was distinct. TP53 mutations were more frequent in T-MN (29.5% versus 7%), while spliceosomal complex mutations were more common in P-MDS (56.5% versus 25.6%).In contrast to P-MDS, the ring sideroblasts (RS) phenotype was not associated with better survival in T-MN, most probably due to genetic association with TP53 mutations. SF3B1 was mutated in 96% of P-MDS with ≥15% RS, but in only 32% T-MN. TP53 mutations were detected in 92% T-MN with ≥15% RS and SF3B1 wild-type cases. Interestingly, T-MN and P-MDS patients with “Very low” or “Low” Revised International Prognostic Scoring System (IPSS-R) showed similar biological and clinical characteristics. In a Cox-regression analysis, TP53 mutation was a poor prognostic factor in T-MN, independent of IPSS-R cytogenetic, disease-modifying therapy and NRAS mutation.Our data have direct implications for T-MN management and provide evidence that, in addition to conventional disease parameters, mutational analysis should be incorporated in T-MN risk stratification.

  Study EGAS00001003547

• Illumina HumanCoreExome genotyping data from the TEENAGE (TEENs of Attica: Genes and Environment) study.

  The TEENAGE study is a cross-sectional study comprising healthy Greek adolescents. The study was conducted according to the guidelines specified in the Declaration of Helsinki and all procedures involving human subjects were approved by the Institutional Review Board of Harokopio University and the Greek Ministry of Education, Lifelong Learning and Religious Affairs. The TEENAGE study target population comprised adolescent students aged 13 to 15 years attending the first three classes of public secondary schools located in the wider Athens area of Attica. The regions across Attica from which students were recruited were physically similar and all urban in nature. Sampling of regions and schools selected to participate was random. Students were enrolled from the wider urban region to ensure that they were coming from families with varying educational background and socio-economic status. Moreover, in order to exclude any vast economic disparities, all participating schools were exclusively public schools, which are free of charge. A total of twenty-four schools participated in the study out of 285 junior secondary public schools in Attica. Anthropometric, medical and dietary information was obtained. DNA samples were genotyped using Illumina HumanCoreExome BeadChips (Illumina, San Diego, CA, USA) at the Wellcome Trust Sanger Institute, Hinxton, UK. Genotypes were called using GenCall (Illumina Genome Studio) followed by zCall and quality control (QC) was performed in two stages (pre- and post-zCall).

  Study EGAS00001001001

• Genomic Alterations in Gingivo-buccal Cancer: ICGC-India Project_YR01

  As a part of the ICGC, India has undertaken genomic studies on gingivobuccal cancer of the oral cavity, which is the most prevalent form of cancer among men in India. There are various known environmental (life-style) correlates of this cancer, the most important of which are tobacco chewing and HPV infection. Paired DNA samples – isolated from the tumor tissue and from the blood of fifty patients – have been analyzed to catalog germline and somatic mutations. Association between each observed genomic alteration and exposure to environmental risk factors is being explored.Detailed clinical characterization of the patients, collection of data on demographic and environmental exposures, and isolation of DNA samples from blood and tumor tissues collected from each patient are being done at the Advanced Centre for Research, Treatment and Education on Cancer, Mumbai. Exome capture and deep resequencing are being performed at the National Institute of Biomedical Genomics, Kalyani. We have analyzed the exomes of paired blood and tumor DNA samples using two orthogonal platforms – exome capture by Roche-Nimblegen SeqCap Ez kit followed by sequencing on Roche-454 GS FLX, and exome capture by Illumina TrueSeq Exome Enrichment kit followed by sequencing on Illumina HiSeq-2000. Each exome is being sequenced at a mean depth of 30x. In addition, we have used Illumina Omni Quad SNP-chips to generate genotype data at 1.14 million genomic markers. The average concordance between SNP-chip and sequence data is 99.8%.

  Study EGAS00001000249

• ICU_transcriptomics__Assessing_the_role_of_the_host_immune_response_in_patients_with_ventilator_associated_pneumonia

  The aim of the proposed project is to provide transcriptomic sequencing data analysis of cells isolated from bronchioalveolar lavage and blood samples from critically ill patients with pneumonia on an intensive care unit in order to investigate the host contribution to disease. The lung microbiome of these patients will be analysed in parallel by deep sequencing and 16S sequencing. These data will provide important information to the development of strategies aimed at improving patient outcomes, reducing the development of antimicrobial resistance and facilitating infection control measures in hospital. Specifically, the proposed work will be a proof of principle study of 100 patients. We will use transcriptomic data to define the host contribution to the symptoms of these critically ill patients diagnosed with pneumonia. The data will be correlated with cytokine/chemokine concentrations, routine microbiology analysis and pathogen genomic data from the same samples to determine the ecology of the lungs of these patients. We will look for associations between clinical features, host response and pathogen genomics in order to identify new diagnostic markers. This study should provide important information to improve the speed and accuracy of diagnosis - resulting in more targeted and successful treatment of critically ill patients in the ICU. 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 EGAS00001003074

• Exploiting evolutionary steering in cancer therapy

  Drug resistance, mediated by intra-tumour heterogeneity and clonal evolution, is arguably the biggest problem in cancer therapy today. However, evolving resistance to one drug may come at the cost of increased sensitivity to another due to so-called evolutionary trade-offs. This weakness can be exploited in the clinic using an approach called ‘evolutionary herding’ that aims at controlling the tumour cell population to delay or prevent resistance. However, model systems able to recapitulate cancer evolution experimentally are lacking and current in vitro techniques based on small populations, re-plating and escalating dose, are unsuitable to develop evolutionary herding strategies. We present a novel methodology for evolutionary herding in vitro and ex vivo using patient-derived organoids. Our approach is based on a combination of single-cell barcoding, very large populations of 108-109 cells grown without re-plating, realistic high drug doses, time-course monitoring of cancer clones, and mathematical modelling of tumour evolutionary dynamics. We demonstrate evolutionary herding in non-small cell lung cancer in vitro and in patient-derived colorectal cancer organoids (PDO). We show that herding causes controlled evolutionary bottlenecks that lead to collateral sensitivity. Through genomic analysis, we were also able to determine the mechanisms that drive such sensitivity. Our approach allows modelling evolutionary trade-offs experimentally to test patient-specific evolutionary herding strategies that can be translated into the clinic to control treatment resistance.

  Study EGAS00001003200

• Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small Cell Lung Cancer

  Tumor mutational burden (TMB) has emerged as a predictive biomarker of response to immune checkpoint inhibitors. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment. Here we evaluate bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples. In CheckMate 026, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne CDx™ assay. TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. Parameter variation can therefore impact TMB calculations, highlighting the need for standardization. Encouragingly, WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90) and differences could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms and centers is achievable.

  Study EGAS00001003661

• Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

  Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via "mapping" procedures to existing data. However, the manual interpretation required in the former case scales poorly to large datasets, which are also often prone to batch effects, while existing data for purified cell types must be available for the latter. Furthermore, unsupervised clustering can be error-prone, leading to under- and over- clustering of the cell types of interest. To overcome these issues we present CellAssign, a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined and de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while simultaneously controlling for batch and patient effects. We demonstrate the analytical advantages of CellAssign through extensive simulations and exemplify real-world utility to profile the spatial dynamics of high-grade serous ovarian cancer and the temporal dynamics of follicular lymphoma. Our analysis reveals subclonal malignant phenotypes and points towards an evolutionary interplay between immune and cancer cell populations with cancer cells escaping immune recognition.

  Study EGAS00001003452

• Genome-wide study of the effect of blood collection tubes on the cell-free DNA methylome

  Background The methylation pattern of cfDNA, isolated from liquid biopsies, is gaining substantial interest for diagnosis and monitoring of diseases. We have evaluated the impact of type of blood collection tube and time delay between blood draw and plasma preparation on bisulfite-based cfDNA methylation profiling. Methods 15 tubes of blood were drawn from three healthy volunteer subjects (BD Vacutainer K2E EDTA spray tubes, Streck Cell-Free DNA BCT tubes, PAXgene Blood ccfDNA tubes, Roche Cell-Free DNA Collection tubes and Biomatrica LBgard blood tubes in triplicate). Samples were either immediately processed or stored at room temperature for 24 or 72 hours before plasma preparation. DNA fragment size was evaluated by capillary electrophoresis. Reduced representation bisulfite sequencing was performed on the cell-free DNA isolated from these plasma samples. We evaluated the impact of blood tube and time delay on several quality control metrics. Results All preservation tubes performed similar on the quality metrics that were evaluated. Furthermore, a considerable increase in cfDNA concentration and the fraction of it derived from NK cells was observed after a 72-hour time delay in EDTA tubes. Conclusion The methylation pattern of cfDNA is robust and reproducible in between the different preservation tubes. EDTA tubes processed as soon as possible, preferably within 24 hours, are the most cost effective. If immediate processing is not possible, preservation tubes are valid alternatives.

  Study EGAS00001004271