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• Samples from the Greek island of Crete, MANOLIS cohort

  Genome-wide association studies of complex traits have been successful in identifying common variant associations, but a substantial heritability gap remains. The field of complex trait genetics is shifting towards the study of low frequency and rare variants, which are hypothesised to have larger effects. The study of these variants can be empowered by focusing on isolated populations, in which rare variants may have increased in frequency and linkage disequilibrium tends to be extended. This work focuses on isolated populations from Greece. Sequencing is very efficient in isolated populations, because variants found in a few samples will be shared by others in extended haplotype contexts, supporting accurate imputation.

  Study EGAS00001000067

• Mutational landscape of eccrine porocarcinoma (sweat gland tumour)

  Eccrine porocarcinoma (EP) is the most common form of sweat gland malignancy. The aetiology of EP is largely unknown. The current lack of data on somatic mutation patterns in EP hampers the development of effective therapies. We performed whole-exome sequencing in a well-characterized sample of 14 matched EP tumour/healthy surrounding tissue samples. Mutational profiling revealed a high overall median mutation rate. This was attributed to signatures of mutational processes related to ultraviolet (UV) exposure, APOBEC enzyme dysregulation, and defective homologous double-strand break repair. All of these processes cause genomic instability and are implicated in carcinogenesis. The analyses revealed alterations in the cancer driver genes and in crucial oncogenic pathways.

  Study EGAS00001004632

• Identification of Therapeutic Targets in Rhabdomyosarcoma Through Integrated Genomic, Epigenomic, and Proteomic Analyses

  Personalized cancer therapy based on the somatic mutations identified in patient tumors is becoming an increasingly emphasized approach to improve outcomes of patients with cancer. There are also examples of therapeutic vulnerabilities in cancer that result from changes in gene expression that are a direct or indirect result of tumor specific epigenetic perturbations. These genomic and epigenomic changes are ultimately manifest in the tumor proteome and phosphoproteome. In this study, we integrated genomic, epigenomic and proteomic data for rhabdomyosarcoma (RMS) to identify therapeutic vulnerabilities. RMS was selected for this analysis because RAS pathway mutations in rhabdomyosarcoma (RMS) are the most common potentially actionable lesions across pediatric solid tumors. The epigenomic data was useful for identifying deregulated developmental pathways in RMS including the WNT, HH, BMP, adenyl cyclase, p38/MAPK and PI3K pathways. Perturbations in those 6 myogenic signal transduction pathways were also evident in the proteome and phosphoteome data. In addition, the proteomic/phosphoproteomic data revealed that the cell cycle checkpoint, unfolded protein response and RB/E2F pathways were deregulated in RMS relative to normal muscle. Recent success targeting CDK4/6 and MEK in adult cancers with RAS mutations led us to test the value of these targets in RMS tumors. We also targeted the unfolded protein response pathway and cell cycle checkpoint pathway using molecular targeted therapeutics in orthotopic patient derived xenografts. Taken together, these data demonstrate the value of integrating epigenomic and proteomic data to identify tumor vulnerabilities that extend beyond somatic mutations identified in the genome.

  Study EGAS00001002967

• Mapping Systemic Lupus Erythematosus Heterogeneity at the Single Cell Level

  Patients with Systemic Lupus Erythematosus (SLE) display a complex blood transcriptome whose cellular origin is poorly resolved. Using single-cell RNA-seq, we profiled ~276,000 PBMCs from 33 children with SLE (cSLE) with different degrees of disease activity (DA) and 11 matched controls. Increased expression of Interferon-stimulated genes (ISGs) distinguished cSLE from healthy control cells. The high-ISG expression signature (ISGhi) derived from a small number of transcriptionally defined subpopulations within major cell types, including monocytes, CD4+ and CD8+ T cells, NK cells, cDCs, pDCs, B cells and especially plasma cells. Expansion of unique subpopulations enriched in ISGs and/or in monogenic Lupus-associated genes classified patients with the highest DA. Profiling of ~82,000 single PBMCs from adult SLE patients confirmed the expansion of similar subpopulations in patients with the highest DA. This study lays the groundwork for resolving the origin of the SLE transcriptional signatures and the disease heterogeneity towards precision medicine applications. Patient demographics, clinical and laboratory data and treatment are summarized and available. The genomic data for participant aHD2 will not be included in the dataset The study description is reprinted from Nehar-Belaid et. al. Nature Immunology, 2020, with permission from Nature Immunology Group

  Study phs002048

• Comparison Between qPCR and RNA-Seq Reveals Challenges of Quantifying HLA Expression

  Human leukocyte antigen (HLA) class I and HLA class II loci are essential elements of innate and acquired immunity. Their exceptional influence on disease outcome is well documented by GWAS and candidate gene studies. The impact of HLA allelic variation on human disease through allele-specific presentation of antigenic peptides to T cells has been the main focus to determine HLA effects on disease susceptibility/pathogenesis. However, HLA expression levels have also been implicated in disease, adding another dimension to the extreme diversity of HLA that impacts variability in immune responses across individuals. HLA expression levels routinely rely on quantitative PCR (qPCR). An alternative is adoption of high throughput technologies such as RNA-Seq. This provides the opportunity to quantify HLA expression in large datasets, but also allows comparison between RNA-Seq and qPCR. In this study, we analyze expression data for HLA Class I genes for a matched set of individuals (N = 96) by RNA-Seq, qPCR and cell surface expression. Samples were obtained from the Research Donor Program (NCI-Frederick). We observed a moderate correlation between RNA-Seq and qPCR. We suggest technical and biological factors that might contribute to differences in the techniques.

  Study phs003177

• DAC for Combined MEK and BCL-2/XL inhibition is effective in high-grade serous ovarian cancer patient-derived xenograft models and BIM levels are predictive of responsiveness

  Dac EGAC00001001250

• NHLBI GO-ESP: Family Studies (JHMI-Molecular Genetics of Atypical Cystic Fibrosis (CF) Study)

  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. Cystic fibrosis (CF) patients without detectable disease-causing mutations in CFTR present a clinical phenotype very similar to, but possibly discrete from, classic CF. We hypothesize that the phenotype of these atypical CF patients is not due only to mutations in the carbonic anhydrase gene CA12 or in the genes encoding the epithelium sodium ion channel ENaC, but is due to mutations in novel genes that have yet to be associated with CF. The goal of this study is to determine the molecular etiology of this atypical CF.

  Study phs000556

• Comparison of structural variations from 10X Genomics linked-reads and conventional Illumina short-reads sequencing

  Structural variations (SVs) are large genomic rearrangements that can drive many diseases. Conventional short-reads whole genome sequencing (cWGS) allows their identification with base-pair resolution, but suffers from high false discovery rate. cWGS taps in short-range information from short-reads while linked-reads sequencing (10XWGS) utilizes long-range information. 10XWGS allows linkage of short-reads originating from the same large DNA molecule with a unique barcode captured in a gel bead in emulsion. This mitigates alignment-based artefacts from cWGS especially in repetitive regions. However, the false discovery rate of this technology is unclear. In this study, we performed a comprehensive analysis of different type and size of SVs predicted from these two technologies. The SVs common between both technologies were found to be highly specific by PCR and Sanger sequencing while validation rate dropped for uncommon events. Further, we propose a novel enrichment approach for filtering out false positive calls from both the technologies independently. To this end, we trained a machine learning model for respective technologies and used it to characterise SVs from MCF7 cell line and a primary breast cancer tumor with high precision. This approach would be valuable in understanding true mechanisms driven by SVs in various diseases.

  Study EGAS00001004093

• Whole_exome_sequencing_of_young_onset_Primary_Sclerosing_Cholangitis

  Primary sclerosing chloangitis is a rare autoimmune disease of the liver (prevalence =10/100,000) with a mean age of onset of 40 years. We are currently undertaking GWASand immunochip experiments to identify loci underlying PSC susceptibility. Through ourcollaborators at the University of Calgary we have access to DNA from three parent-offspringtrios where the children required liver transplants due to PSC before the age of 9. These areextremely rare cases indeed and we believe that exome-sequencing represents a powerfulmeans of identifying the causal mutation underlying this severe phenotype.

  Study EGAS00001000388

• Neutrophils and emergency granulopoiesis drive immune suppression and an extreme response endotype during sepsis

  This dataset contains raw sequencing files associated with the paper "Neutrophils and emergency granulopoiesis drive immune suppression and an extreme response endotype during sepsis" (https://doi.org/10.1038/s41590-023-01490-5). It is composed of two experiments, which are as follows: 1. Single-cell profiling of whole blood leukocytes: This experiment comprises sequencing files generated using the BD Rhapsody single-cell multi-omics profiling (RNA + protein) platform. This platform was used to profile the whole blood leukocyte population in a cohort of sepsis patients, cardiac surgery controls and healthy controls. There are 48 samples and four files per sample: two paired-end FASTQ files (R1 and R2) corresponding to the RNA-seq library, and two paired-end FASTQ files (R1 and R2) corresponding to the protein profiling (ADT-based AbSeq) library. 2. Single-cell profiling of circulating HSPCs: This experiment comprises sequencing files generated using the 10X single-cell multi-omics (RNA-seq + ATAC-seq) profiling platform. This platform was used to profile circulating HSPCs in a cohort of sepsis patients and healthy controls. There are 5 samples (or plexes), each of which consists of a pool of individuals for whom cells were multiplexed and sequenced as a single sample. There are four files per sample: two paired-end FASTQ files (R1 and R2) corresponding to the RNA-seq library, and two paired-end FASTQ files (R1 and R2) corresponding to the ATAC-seq library. Because these samples consists of multiplexed pools, index files are also provided. These can be used for sample deconvolution using the Cell Ranger pipeline. NOTE: Due to EGA's constrains in the number of files permitted per sample, index files (I1 and I2) for the HSPC data set are provided as a separate experiment named "FASTQ index files (I1 and I2) for deconvolution of 10X single-cell multiomics libraries".

  Dataset EGAD00001010927