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• SCI-MAP: Single Cell Microgel embedded iPS-cells to map molecular variability of cell differentiation using a systems biology approach.

  In the SCI-MAP project we will map cell states encountered across a previously established 49 day in vitro chondrogenic differentiation protocol. We do this to optimise the differentiation process for therapeutic and in vitro modelling ends. We collect epigenetic open chromatin and phenotypic transcriptome data to determine cell states and so performed single nucleus sequencing in two modalities: RNA- and ATAC-sequencing. Data was collected in a time series experiment at 7 points: Days 0, 3, 6, 8, 14, 21, and 49, starting with the first pilot data from day 21 (D21).

  Study EGAS50000001041

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

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

  Study EGAS50000001297

• Primary plasma cell leukemia (pPCL) samples were sequenced using the Nimblegen MedExome hybridization capture to detect translocations, copy number changes, and mutations in 20 pPCL samples and patient matched controls.

  Primary plasma cell leukemia (pPCL) is a rare malignancy related to multiple myeloma. Here we have assembled 20 patient samples and performed whole exome sequencing to determine the differences between multiple myeloma and pPCL. CD138+ cells were purified from bone marrow aspirates from patients with pPCL. Control cells were obtained from CD34+ stem cell harvests or CD3+ T cells. DNA was extracted and processed using the HyperPlus library prep kit (KAPA Biosystems) and sequenced using 75 bp paired end reads on an Illumina NextSeq500.

  Study EGAS00001003104

• Psoriasis Patient PBMC scRNA-seq data

  This dataset contains raw and processed data of four scRNA-seq PBMC samples from four Psoriasis patients (Pso3 = male, Pso4 = female, Pso7 = female, Pso8 = male). Raw sample libraries were prepared with 10x 5'-kit v2 multiplexing the individual samples using TrueSeq barcoded antibodies to stain the cells. Resulting sequencing data consists of four FASTQs (2 x antibody multiplex to demultiplex the samples + 2 x transcriptome data containing the typical cell x UMI barcode data for count matrix generation). The raw sequencing data was processed with cellranger 6.0.1 with the GRCh38 3.0.0 reference and cell to sample assignment was subsequently done with couhto 1.1.0 (https://github.com/dmalzl/counhto) employing the same algorithm as cellranger multi (couldn't be used here though as multi does not handle 5'-chemistry data). Processed data contains all main outputs of cellranger count in raw text format or in h5 formats including the used feature reference for (i.e. antibody barcode to sample assignment) as well as the computed cell to sample assignment computed by counhto. For further details including all used code in the analysis of the data please consult https://doi.org/10.5281/zenodo.13846873

  Dataset EGAD50000001102

• Use of Deep Sequencing to Dectect Clonal Mutations In Sun Exposed Skin Epidermis

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Dataset EGAD00001001090

• Co-amplification of MYC and CCNE1 in aggressive childhood osteosarcoma

  Osteosarcoma, the most common primary malignant tumour of bone, affects children and adults alike. No fundamental biological differences between paediatric and adult osteosarcoma are known. Here, we apply multi-region whole genome sequencing to an index case of a four-year old child whose aggressive tumour harboured high level, focal amplifications of MYC and CCNE1 connected by translocations. We re-analysed copy number readouts of 258 cases of high-grade osteosarcoma from three different cohorts and identified an additional three cases with MYC and CCNE1 co-amplification, confined to children and associated with aggressive disease. Examining the age distribution of MYC and CCNE1 amplicons across all cases revealed a significant enrichment of focal MYC amplification in children, whereas CCNE1 amplification is not strictly restricted to children. Our findings indicate that amplification of the MYC oncogene, known to be associated with a poor outcome, delineates a variant of osteosarcoma specific to childhood. When co-amplified with CCNE1, it may herald an aggressive disease course.

  Dataset EGAD00001006859

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006642

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006643

• POETIC clinical Trial Ki67 Bookend Breast Cancer Targeted Exome and RNAseq Project

  Using RNAseq, we compare the 15% of poorest responders (PRs, n=177) as measured by proportional Ki67 changes after 2 weeks of neoadjuvant aromatase inhibitors to good responders (GRs, n=190) selected from the top 50% responders in the POETIC trial and matched for baseline Ki67 categories. In the POETIC trial, 4,480 postmenopausal women with primary ER+ BC were randomised 2:1 to receive either treatment with a non-steroidal AI (letrozole or anastrozole) for 2 weeks before and 2 weeks after surgery or to no perisurgical treatment. Only AI-treated patients with HER2- tumors, paired baseline and surgery Ki67 available, and baseline Ki67 immunohistochemistry (IHC) >10% (to minimise imprecision in proportional Ki67 falls) were included for selection. Data is baseline RNAseq and targeted exome DNA sequencing analysis of POETIC Good/Poor Responders to aromatase inhibitors based on change in Ki67.

  Dataset EGAD00001010919

• Whole blood RNA sequencing of individuals from Nepal

  This study utilized blood samples collected in Lalitpur, Nepal as part of the Strategic Typhoid Alliance across Africa and Asia (STRATAA) study. The dataset comprises whole blood RNAseq of 376 febrile individuals from Nepal. Blood was collected in PAXgene tubes and sent to Monash University (Melbourne, Australia) where RNA was extracted using the PAXgene Blood RNA kit before being sent to the Wellcome Sanger Institute (Hinxton, UK) for sequencing. Library prep used NEBNext Ultra II RNA custom kits on an Agilent Bravo WS automation platform with poly(A) pulldown. After PCR, plates were purified using Agencourt AMPure XP SPRI beads and libraries were quantified using Biotium Accuclear Ultra high sensitivity dsDNA Quantitative kits. Pooled libraries were normalised to 2.8 nM. Samples were globin depleted using KAPA RNA HyperPrep with RiboErase. Libraries were then subjected to 2x100bp paired-end sequencing on Illumina NovaSeq. Each library was sequenced to an average of 80 million reads. The STRATAA study was approved by the Nepal Health Research Council (NHRC, ref 283 306/2015) and OxTREC (Oxford Tropical Research Ethics Committee, ref 39-15). All participants provided informed consent for human genetic tests.

  Dataset EGAD00001011131

• WGS dataset of Mutational Mechanisms in Multiply Relapsed Pediatric Acute Lymphoblastic Leukemia

  Pediatric acute lymphoblastic leukemia (ALL) is marked by low mutational load at initial diagnosis, which increases at relapse. The elevated mutational load at relapse can partly be explained by at least two therapy-related effects and a combination of therapy and underlying mismatch repair deficiency. However, our understanding of the type and timing of mutational mechanisms in relapsed ALL is limited, and it is unclear to what extent mutational processes contribute to disease progression. We collected a cohort of 29 Dutch ALL patients across multiple treatment protocols who had multiple relapses. Using whole genome sequencing of the sequential tumor samples of each patient we were able to distinguish the mutational processes active in relapsed ALL and could track the activity of mutational processes over time. This allowed us to investigate whether subtype-specific mutational processes at diagnosis can continue in relapse or emerge at relapse if absent in initial diagnosis. Furthermore, we assessed whether the activity of mutational processes contributed to disease development and relapse.

  Dataset EGAD00001015401

• NHGRI Genome Integrity of iPSCs Study

  The purpose of this study is to compare mutation load in induced pluripotent stem cells derived from skin fibroblasts.

  Study phs001277

• AmsterdamUMC Data Access Committee for the EPIC-CD study

  The current data access committee reviews and assesses data requests of researchers that seek to gain access to data acquired as part of the EPIC-CD project as performed at the AmsterdamUMC, Amsterdam, Netherlands.

  Dac EGAC50000000097

• DNA methylation array study for 7 pairs of primary NSCLCs and distant metastases

  This study is to compare DNA methylation profiles between primary NSCLCs and paired distant metastases.

  Study EGAS00001004079

• Mutational_Screening_of_Human_Acute_Myleloid_Leukaemia_Samples

  Characterization of somatic mutations in Acute Myeloid Leukaemia samples to identify whether they can be classified into three mutually exclusive groups.

  Study EGAS00001000046

• PREDICT___Whole_Genomes

  PREDICT/Predicting individual response and resistance to VEGFR/mTOR pathway therapeutic intervention using biomarkers discovered through tumour functional genomics.

  Study EGAS00001000934

• Long-read RNA sequencing of human normal liver organoid with or without SF3B4 overexpression

  Project aims to find alternative splicing events and resulting transcript isoforms modulated by SF3B4

  Study EGAS50000000849

• ChIP-seq in colorectal cancer and paired adjacent normal mucosa

  Chip-seq samples for 20 colorectal patients with paired adjacent normal mucosa to characterize H3K27ac and H3K4me1.

  Study EGAS00001005303

• Star-based RNA count files

  To ellucidate gene activity in mRCC, RNA Sequencing data was generated as part of the EuroTarget study. Star aligner 2.7 was used to generate count files

  Dataset EGAD50000002296

• Bulk transcriptomics of Human High-Grade-B-Cell-Lymphomas differentiated according to IGH status

  GCB DLBCL MB2 DE and HGBCL-DH-BCL2(-BCL6) cases classified according to IGH status in IGH+ or IGH-undetectable

  Dataset EGAD50000001524

• Melanoma Germlines subset for BAP1

  These samples comprise both melanoma cases and controls sequenced for a selection of loci linked to disease susceptibility. These bams are a subset of the sequencing restricted specifically to the GRCh37 coding areas of the BAP1 gene.

  Dataset EGAD00001002743

• Discovering the Genetic Basis of Human Neuroblastoma: A Gabriella Miller Kids First Pediatric Research Program (Kids First) Project

  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). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Children with disseminated neuroblastoma have a very high risk of treatment failure and death despite receiving intensified chemotherapy, radiation therapy and immunotherapy. The long-term goal of our research program is to ultimately improve neuroblastoma cure rates by first comprehensively defining the genetic basis of the disease. The central hypothesis to be tested here is that neuroblastoma arises largely due to the epistatic interaction of common and rare heritable DNA variation. Here we will perform a comprehensive whole genome sequencing of 563 quartets of neuroblastoma patient germline and diagnostic tumor DNAs and germline DNAs from both parents. The case series was recently collected through a Children's Oncology Group epidemiology clinical trial and is robustly annotated with complete demographic (age, sex, race, ethnicity), clinical (e.g. age at diagnosis, stage, risk group), epidemiologic (parental dietary and exposure questionnaire) and biological (e.g. tumor MYCN status and multiple other tumor genomic measures) co-variates. Subjects were consented for genetic research and DNA is immediately available for shipment for sequencing. We propose Illumina-based whole genome sequencing in the 593 "trio" germline samples (Aim 1; due to missing parent: 487 full neuroblastoma triads, 106 child-single parent dyads = 1673 whole genome sequences) and matched diagnostic tumor DNA (Aim 2; N=366) at 30x sequencing depth (N=2039 whole genome sequences). Also in Aim 2 we will perform whole exome (100x) and RNA sequencing on the 366 tumor DNA and 228 tumor RNA samples from this cohort. Finally, we propose a pilot study of structural variation using long-range sequencing in 10 non-overlapping tumor samples chosen based on potentially relevant chromosomal alterations discovered with conventional NGS. Thus, a total of 2277 individual samples and 2655 sequences will be generated. We will use our established analytic pipeline that is currently being used to study the germline genomes of all cases sequenced through the NCI supported Therapeutically Applicable Research to Generate Effective Treatments program. We plan a three-stage analytic approach, first focusing on classic de novo and inherited Mendelian damaging alterations. We will next integrate our extensive epigenomic data from human neuroblastoma cell lines and genome-wide association study data (N=5,703 neuroblastoma cases to date) to guide a comprehensive assessment of noncoding variants that influence tumor initiation with a recently established analytic pipeline. Finally, we will utilize the tumor DNA analyses to inform relevance via somatic gain or loss of function effects at the sequence and/or copy number levels. All data generated in this project will be immediately placed into the Genomic Data Commons (GDC) and we will compute within this environment by importing our analytic pipelines into the GDC. These data will be fully integrated into the Kids First Data Resource and freely shared with all academically qualified petitioners. This comprehensive data set derived from a large and richly phenotyped series of neuroblastoma DNA quartets will be integrated with existing germline and/or tumor genomic data from over 6,000 neuroblastoma subjects (but none with matched patient-parent germline sequencing data) to provide an unparalleled opportunity to comprehensively discover the genetic basis of neuroblastoma.

  Study phs001436

• Genome-Wide Association Study of Hypertriglyceridemia in Mexicans

  Coronary artery disease (CAD) is the number one cause of death and mortality world-wide. High levels of serum triglycerides (TGs) and low levels of serum high-density lipoprotein cholesterol (HDL-C) are major risk factors for CAD. Previous epidemiological studies have shown that these two lipid disturbances are highly common dyslipidemias in Mexicans. However, the genetic factors underlying high serum TGs and low HDL-C are underinvestigated and poorly identified in Mexicans. As the Mexican-American and the genetically related Latin-American populations represent the fastest growing minority in the United States, elucidation of the unknown genetic factors influencing the increased susceptibility of Mexicans to these common dyslipidemias is of great relevance to these U.S. minorities and the American healthcare system. This study is a research collaboration between investigators at the University of California, Los Angeles (UCLA) and Instituto Nacional de Ciencias Médicas y Nutrición (INCMN), Mexico City, to perform a two-stage genome-wide association study (GWAS) for hypertriglyceridemia and low high-density lipoprotein cholesterol (HDL-C) in Mexicans (Weissglas-Volkov et al. 2013, PMID: 23505323). This study was funded by an RO1 grant from NIH/NHLBI (PI Paivi Pajukanta; PI of the subaward Teresa Tusie-Luna). In stage 1 of the GWAS, we tested all GWAS SNPs from the Illumina Infinium Human610-Quad platform that passed quality control for association in ~2,200 hypertriglyceridemia cases and controls. In stage 2, we genotyped the ~1,200 positive signals of stage 1 in additional ~2,200 hypertriglyceridemia cases and controls, and performed a combined analysis of the two stages to identify genome-wide significant variants. The subjects were recruited at the INCMN. The DNA isolation and clinical laboratory measurements of the case-control study samples were performed at INCMN using standardized procedures. Genotyping and statistical analyses of the data were performed at UCLA. A summary of this GWAS can be found in Weissglas-Volkov et al. 2013 Journal of Medical Genetics, PMID: 23505323. Briefly, using the two-stage GWAS design, we identified a novel Mexican-specific genome-wide significant locus for serum TG levels close to the Niemann-Pick type C1 protein (NPC1) gene (Weissglas-Volkov et al. 2013, PMID: 23505323). Of the European lipid GWAS loci, three TG loci (APOA5, GCKR, and LPL) and four HDL-C loci (ABCA1, CETP, LIPC and LOC55908) resulted in genome-wide significant signals in Mexicans. Furthermore, our cross-ethnic mapping narrowed three European TG GWAS loci, APOA5, MLXIPL, and CILP2 that exhibited long range LD and a large number of candidate SNPs in the European GWAS scan. In the apolipoprotein A1C3A4A5 gene cluster region, the cross-ethnic fine mapping and LD comparisons reduced the number of candidate variants to one SNP, rs964184. We also found that although 52% of the associations from European lipid GWAS meta-analysis could be generalized to Mexicans, in 82% of the European GWAS loci, a different variant other than the European lead SNP provided the statistically strongest evidence of association in the Mexican scan (Weissglas-Volkov et al. 2013, PMID: 23505323). Taken together, our Mexican GWAS for lipids identified a novel Mexican-specific locus for high serum TGs; restricted three European GWAS loci; and investigated which European lipid GWAS variants extend to the Mexican population (Weissglas-Volkov et al. 2013, PMID: 23505323). This NHLBI sponsored RO1 project aimed to identify genetic variants contributing to serum lipid levels in Mexicans. In addition to de-identified genome wide genotypic data, a selected list of de-identified phenotypic data related to hypertriglyceridemia and related metabolic traits are also available in dbGaP.

  Study phs000618

• eMERGE: Northwestern (NUgene) WGS

  The NUgene Project is a biorepository with longitudinal medical information from participating patients at Northwestern Medicine affiliated hospitals and outpatient clinics. Participants' DNA samples are coupled with data from a self-reported questionnaire (2 versions were used, 1 before and 1 after February 2006, both are included) and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 3 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated enterprise data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. The electronic MedicalRecords and Genomics (eMERGE) Network is a consortium of 9 clinical sites with EMR linked DNA biobanks, including Northwestern University and its NUgene biobank, funded by the NHGRI (National Human Genome Research Institute) to investigate the use of electronic medical record systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 100,000 individuals using EMR-derived phenotypes and DNA from linked biorepositories. Using electronic phenotyping methods, the consortium has been and is using DNA samples from all participating sites to explore the genetic determinants of approximately 80 phenotypes, including both diseases and traits, for which the electronic phenotyping algorithms have or are being published on PheKB.org. Thus, for the eMERGE network, ~900 NUgene subjects were selected, as described in the study inclusion/exclusion criteria section below, to be genotyped using whole genome sequencing (WGS), for use in the eMERGE network as eMERGE subjects. The criteria used below were selected so that these subjects will likely meet the criteria to be cases and/or controls, of diverse races and/or ethnicities, for at least 1 of the ~80 phenotypes being studied within eMERGE, and could be recontacted for future research if needed.

  Study phs001191

• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK): Identification of VUR genes by exome sequencing

  Primary vesicoureteric reflux (PVUR), or non-syndromic VUR, is the most common type of congenital anomaly of the kidney and the urinary tract (CAKUT). PVUR is the single most important risk factor for pyelonephritis and renal parenchymal scarring in the pediatric age group. Renal parenchymal scarring due to PVUR is referred to as reflux nephropathy and is a major cause of end stage kidney disease requiring dialysis and kidney transplantation in children. PVUR shows familial aggregation; however, the specific genetic cause(s) of PVUR is unknown despite a number of linkage studies. Reasons for this include: variable expression of the disease, difficulty with case ascertainment, genetic heterogeneity and lack of large pedigrees that can facilitate locus identification. We have ascertained a large 97 member PVUR kindred spanning five generations. We performed a genome-wide linkage study (GWLS) on this family and obtained a significant genome-wide LOD score of 3.3 on chromosome 6p. We performed exome sequencing on affected individuals in the family and identified mutations in tenascin XB (TNXB) as a cause of familial VUR. The proposed studies have the following specific objectives: a) to define the role of tenascin genes in the etiology of PVUR, and b) to identify new PVUR causative genes. Our specific aims are (1) To perform mutation analysis in TNXB and other tenascins in a cohort of 200 individuals with familial and sporadic PVUR and define genotype/phenotype correlations. (2) To perform sequential genome wide linkage studies (GWLS) and whole exome/targeted sequencing in families with PVUR. Impact on public health: Identification of PVUR genes may provide a novel non-invasive diagnostic tool for a subset of children with PVUR. Furthermore, this research will provide insights into the pathogenesis of PVUR and further elucidate the pathways involved in the development of the kidney and genitourinary tract. Future studies will define the role of the genes in the etiology of other malformations of the kidney and urinary tract and also seek to unravel the mechanisms by which the identified gene causes PVUR and other malformations of the kidney and the urinary tract.

  Study phs000778