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• 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

• 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

• 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

• 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

• 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

• 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

• 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

• TOPDECC-Trans-omics for Precision Dentistry and Early Childhood Caries: Genome-Wide Genotyping (CIDR) and Microbiome in the ZOE 2.0 Study

  The ZOE 2.0 study is a cross-sectional genetic epidemiologic investigation of early childhood oral health, conducted in a state-wide, community-based, multi-ethnic sample of 3-5-year-old preschool-age children in North Carolina, United States. Between 2016-2019, 8,059 children were enrolled and 6,404 of them underwent comprehensive oral-clinical examinations that provided usable data on dental caries (i.e., early childhood caries; ECC) phenotypes. Saliva samples and supragingival biofilm samples were collected by 10 trained and calibrated examiners during the clinical encounters that took place in enrolled children's preschool (Head Start) centers. Specifically, the study enrolled participants and conducted clinical examinations in 260 Head Start centers that belonged to 34 Head Start programs in NC. 6,262 participants provided clinical data and had extracted DNA that met quantity and quality criteria for high-density genotyping and 6,144 of them were retained in the genome-wide association study (GWAS). Additional information on oral health-related behaviors, risk factors and self-reported outcomes was collected prior to the conduct of the clinical exam using self-administered questionnaires completed by children's guardians. Height and weight measurements were used to derive measures of adiposity. A domestic water sample for fluoride concentration measurement was obtained after the clinical examination for approximately 25% of study participants, to provide a measure of environmental exposure to this known caries-preventive agent and this information was subsequently imputed to the entire cohort using a novel GIS-informed method. Supragingival biofilm samples for microbiome analyses were collected from all participating children. Biofilm samples from a pilot 5% (n=300) of the cohort were carried forward to WGS (metagenomics; MTG) and RNAseq (metatranscriptomics; MTX) analyses, and these sequence data are being released via the Sequence Read Archive (SRA) in this dbGaP accession: 300 participants with MTG, 297 of those with MTX. Of note, the 17 participants with MTG data did not have genotypes produced, therefore the study's released participant total count is 6161, including 6144 (with genotypes released) plus 17 (with no genotypes released but with MTG data in the SRA).The study's primary objective is to identify risk loci and gene sets/pathways for ECC and related traits (e.g., caries prevalence and severity) by conducting a trans-ethnic GWAS. Genotyping is based on the Infinium™ Global Diversity Array and the TOPMed panel is used for imputation via the University of Michigan Imputation server. Secondarily, the ZOE 2.0 seeks to determine prevalence and severity of dental caries, other oral disease outcomes, and putative risk factors for dental caries in this low-income population-based sample of European-, African-, and Hispanic/Latino-American preschool-age children.

  Study phs002232