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• Multiplexing cortical brain organoids for the longitudinal dissection of developmental traits at single cell resolution

  Dissecting human neurobiology at high resolution and with mechanistic precision requires a major leap in scalability, given the need for experimental designs to multiple individuals and, prospectively, population cohorts. To lay the foundation for this, we have implemented and benchmarked complementary strategies to multiplex brain organoids by pooling cells from different pluripotent stem cell lines (PSC) either during organoid generation (mosaic models) or before single cell-RNAseq library preparation (downstream multiplexing). We have also developed a new computational method, SCanSNP, and a consensus call to deconvolve cell identities, overcoming current criticalities in doublets prediction and low quality cells identification. We validated both multiplexing methods for charting neurodevelopmental trajectories at high resolution, thus linking specificity to genetic variation. Finally, we modelled their scalability across different multiplexing combinations and showed that mosaic organoids represent an enabling method for high-throughput settings. Together, this multiplexing suite of experimental and computational methods provides a highly scalable resource for disease modelling.

  Study EGAS50000000698

• MP2PRT: Genomic and Molecular Characterization of Biomarkers Associated with Tumor Angiogenesis, DNA Repair, and Immunologic Tolerance using Samples from the NRG Oncology Phase 3 Randomized Trial, GOG-0240 (NCT00803062)

  The Molecular Profiling to Predict Response to Treatment (MP2PRT) program is part of the NCI's Cancer Moonshot Initiative. The aim of this program is the retrospective characterization and analysis of biospecimens collected from completed NCI-sponsored trials of the National Clinical Trials Network and the NCI Community Oncology Research Program. This study is one of the selected studies under this program. For this study, genomic characterization (WGS, WXS, Total RNAseq, miRNAseq) has been performed on cervical tumor tissue from patients with advanced disease (persistent, recurrent, and metastatic) and matching germline samples. It is hypothesized that the characterization of these tissues using next generation sequencing will lead to the identification of relevant novel genetic aberrations within the immunologic, DNA repair, and tumor angiogenesis domains that dichotomize the study population into exceptional responders and non-responders to systemic therapy, with a spectrum of response manifesting between the two extremes.

  Study phs002293

• Single cell sequencing data of PBMC and CSF from a cohort of Multiple Sclerosis patients and other neurological disease controls

  Neuroinflammation is often characterised by immune cell infiltrates in the cerebrospinal fluid (CSF). Here we apply single-cell RNA sequencing to explore the functional characteristics of these cells in patients with various inflammatory, infectious and non-inflammatory neurological disorders. We show that CSF is distinct from the peripheral blood in terms of both cellular composition and gene expression. We report that the cellular and transcriptional landscape of CSF is altered in neuroinflammation, but is strikingly similar across different neuroinflammatory disorders. We find clonal expansion of CSF B and T cells in all disorders but most pronounced in inflammatory diseases, and we functionally characterise the transcriptional features of these cells. Finally, we explore the genetic control of gene expression in CSF lymphocytes. Our results highlight the common features of immune cells in the CSF compartment across diverse neurological diseases and may help to identify new targets for drug development or repurposing in Multiple Sclerosis.

  Study EGAS50000000739

• MP2PRT-MNG: Identifying Novel Molecular Markers of Response to Radiotherapy in Meningiomas Using Samples from the RTOG-0539 (NCT00895622)

  The Molecular Profiling to Predict Response to Treatment (MP2PRT) program is part of the NCI's Cancer Moonshot Initiative. The aim of this program is the retrospective characterization and analysis of biospecimens collected from completed NCI-sponsored trials of the National Clinical Trials Network and the NCI Community Oncology Research Program. NRG RTOG (Radiation Therapy Oncology Group)-0539, which was a nonrandomized phase II cooperative group trial in 2009, was selected for inclusion in this program. NRG RTOG-0539 assigned patients with histologically confirmed diagnosis of meningioma to 1 of 3 risk groups based on 2007 WHO grade, resection extent, and recurrence status, and radiotherapy was given per protocol to the intermediate- and high-risk cases. Under the MP2PRT program, DNA methylation profiling, RNA sequencing, and whole exome sequencing were performed on clinical trial cases with available tissue for molecular analyte extraction and subsequent sequencing. Raw molecular data with metadata are available for this study.

  Study phs003707

• DNA methylation and transposable element landscapes define human regulatory T cells in tissues and identify their blood recirculating counterpart

  Regulatory T cells (Treg cells) in tissues can perform immunoregulatory and tissue-regenerative functions. Despite these important tasks, human-tissue Treg cells lack understanding, specifically, the epigenetic basis of their differentiation as well as re-circulating tissue-Treg cells are incompletely understood. Here, we performed genome-wide DNA methylation analysis of human Treg cells from skin and blood and embedded this in a multi-omic epigenetic framework including chromatin accessibility and gene-expression. We thereby revealed novel epigenetic programs defining human skin Treg cell differentiation and delineated how these are present on the different epigenetic levels. We discovered that transposable elements are an integral constituent of the demethylation landscape in skin Treg cells. Based on TCR-sequencing and DNA demethylation homologies, our data unveil that blood CCR8+ Treg cells are recirculatory human tissue-Treg cells. Our data provide novel insights in human tissue-Treg biology, required to harness these cells for therapeutic avenues.

  Study EGAS50000000738

• High Resolution Maps of the HeLa 3D Genome Using Hi-C

  We use in situ Hi-C to probe the three-dimensional architecture of genomes, constructing haploid and diploid maps of nine cell types (including HeLa). The densest, in human lymphoblastoid cells, contains 4.9 billion contacts, achieving 1-kilobase resolution. We find that genomes are partitioned into contact domains (median length, 185kb), which are associated with distinct patterns of histone marks and segregate into six subcompartments. We identify ~10,000 loops. These loops frequently link promoters and enhancers, correlate with gene activation, and show conservation across cell types and species. Loop anchors typically occur at domain boundaries and bind CTCF. CTCF sites at loop anchors occur predominantly (>90%) in a convergent orientation, with the asymmetric motifs 'facing' one another. The inactive X-chromosome splits into two massive domains and contains large loops anchored at CTCF-binding repeats. The data for the other (non-HeLa) cell types has been uploaded to GEO.

  Study phs001010

• Genomic Landscape of Apical Periodontitis

  We undertook the first genome-wide association (GWAS) study of apical periodontitis, enrolling 932 patients with deep carious lesions at UTHealth School of Dentistry and the University of Pittsburgh School of Dental Medicine. We used a case-control design to compare those with apical periodontitis to those without. Genotype data was generated for all participants and imputed using the TOPMed reference panel. We performed a single-variant association testing, a subphenotype analysis, and a genetically regulated expression association analysis, and generated a polygenic risk score and performed phenome-wide association analysis. We identified eight near-genome-wide significant loci for our primary outcome, eight genes where genetically regulated expression was associated with apical periodontitis status, and 33 phecodes that were associated with the generated polygenic risk score. We also replicated three loci previously reported in the literature. Genotype, phenotype, and results from the primary association analysis will be available via dbGaP.

  Study phs003252

• Pooled Mutant KRAS-Targeted Long Peptide Vaccine Combined with Nivolumab and Ipilimumab for Patients with Resected MMR-p Colorectal and Pancreatic Cancer

  We developed INtraCEllular Reverse Transcription with Sorting and sequencing (INCERTS), an approach to combine molecular indexing of receptor repertoires within intact cells and fluorescence-activated cell sorting (FACS). We demonstrate that INCERTS enables efficient processing of millions of cells from pooled human peripheral blood mononuclear cell (PBMC) samples while retaining robust association between T cell receptor (TCR) sequences and cellular phenotypes. We used INCERTS to discover antigen-specific TCRs from patients with cancer immunized with a novel mutant KRAS peptide vaccine. After ex vivo stimulation, 28 uniquely barcoded samples were pooled prior to FACS into peptide-reactive and non-reactive CD4+ and CD8+ populations. Combining complementary patient-matched single-cell RNA sequencing (scRNA-seq) data enabled retrieval of full-length, paired TCR alpha and beta chain sequences for future validation of therapeutic utility. Data available through dbGaP include scRNA-seq with matched TCR-seq.

  Study phs003425

• Efficient prediction of a spatial transcriptomics profile better characterizes breast cancer tissue sections without costly experimentation

  Spatial transcriptomics is an emerging technology requiring costly reagents and considerable skills, limiting the identification of transcriptional markers related to histology. Here, we show that predicted spatial gene-expressions in unmeasured regions and tissues can enhance biologists��� histological interpretations. We developed the Deep learning model for Spatial gene Clusters and Expression, DeepSpaCE and confirmed its performance using the spatial-transcriptome profiles and immunohistochemistry images of consecutive human breast cancer tissue sections. For example, the predicted expression patterns of SPARC, an invasion marker, highlighted a small tumor-invasion region that is difficult to identify using raw data of spatial transcriptome alone because of a lack of measurements. We further developed semi-supervised DeepSpaCE using unlabeled histology images and increased the imputation accuracy of consecutive sections, enhancing applicability for a small sample size. Our method enables users to derive hidden histological characters via spatial transcriptome and gene annotations, leading to accelerated biological discoveries without additional experiments.

  Study JGAS000290

• Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedNanoSeq_Blood

  Utilising Targeted NanoSeq, we hope to explore the driver landscape in unprecedented detail in donors from TwinsUK. These donors have paired buccal swabs and data from this will help contextualise that work. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015619