7188 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

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• Osteosarcoma_RNAseq

  We propose to definitively characterise the somatic genetics of Osteosarcoma cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome and transcriptome sequencing.

  Study EGAS00001000615

• Bulk RNAseq of paired IDHwt GBM

  64 paired-end Illumina RNAseq whole transcriptome stranded libraries from 32 pairs of matched primary and recurrent GBM

  Dataset EGAD00001009806

• 16 Year Life History and Genomic Evolution of an ER+ HER2- Breast Cancer

  Case report of an ER+ Her2- breast cancer patient. Whole exome and transcriptome sequencing at time of diagnosis and relapse, targeted DNA sequencing of a liver met

  Dataset EGAD00001006365

• Transcriptome analysis of CD8 T-cells from blood, fat, liver and skin

  CD8 Tcells were FACS sorted and processed with 10x Genomics Chromium Next GEM SingleCell V(D)J Reagents Kits v1.1 sequencing. In total 6 samples were processed. Fastq files are supplied.

  Dataset EGAD00001010007

• Transcriptome analysis of Tcells from blood, fat and skin

  Tcells were isolated fom Tissues and FACS sorted. In total 50 samples were processed in 5 replicates with the Takara SmartSeq Stranded kit. Single end fastq-files are supplied.

  Dataset EGAD00001007663

• Genomic and transcriptomic profiling of soft tissue sarcoma

  We characterized soft tissue sarcoma by targeted gene panel sequencing (MSK-IMPACT) and transcriptome profiling to discover biological mechanisms under metastatic progression.

  Dataset EGAD50000000846

• Diverse transcriptomic and mutational patterns but limited functional pathway alterations in patient-derived SS cells

  We profile the whole-transcriptome of 7 patient-derived Sézary Syndrome (SS) cells to identify expression patterns, functional programs and expressed gene mutations that may provide clues on new therapeutic options for SS patients. The libraries were sequenced on NextSeq500 (Illumina) with a paired-end read length of 2x75bp.

  Study EGAS50000001151

• Transcriptome analysis of Williams syndrome

  Williams syndrome (WS) is a neurodevelopmental disorder caused by microdeletion on chromosome 7q11.23, and has attracted much attention for its distinctive features, such as hypersociability. However, it remains unclear which genes are involved in the complex phenotypes of their condition. Here, we performed transcriptome analysis of peripheral blood to identify genes associated with WS.

  Study JGAS000132

• Comprehensive genetic analysis of pediatric germ cell tumors

  Germ cell tumors (GCTs) are relatively rare tumors in children. Previous studies showed that adult testicular GCTs had some genomic alterations, but genetic basis of pediatric GCTs is still to be elucidated. We applied DNA methylation array analysis, whole-transcriptome sequencing, targeted capture sequencing, and SNP array analysis to fifty-one GCT samples.

  Study JGAS000204

• The_Transcriptome_of_PLX4032_resistance

  We have collected material from a patient who had BrafV600E mutant melanoma that wastreated with PLX4032. We have germline DNA from the patient and DNA and RNA fromdistinct lesions before and after treatment with PLX4032. We have transcriptome sequenced these samples to obtain a snap shot of the mechanisms of resistance that are operative.

  Study EGAS00001000413

• atrial appendage miRNA-seq in non-, paroxysmal and persistent atrial fibrillation

  64 left atrial appendages from patients without atrial fibrillation (AF) undergoing cardiac surgery, patients with paroxysmal AF and with persistent AF (~20 per group). Trizol RNA isolation, size selection, single end miRNA sequencing on 4 lanes of illumina NextSeq 500. Provided are FastQ files, one per lane per sample. Additional data (e.g. clinical characteristics, RIN values etc.) can be provided upon request. The same RNA samples (62) were used for transcriptome sequencing. Results from transcriptome sequencing are stored in the EGA database and are managed by the same DAC.

  Dataset EGAD00001007694

• Spatial transcriptome sequence data from HER2-positive human breast tumors (n=8, with 3 or 6 sections from each)

  Spatial transcriptome sequence data from HER2-positive human breast tumors obtained from the first generation of Spatial Transcriptomics arrays. The dataset contains 8 different tumors with 3 or 6 sections taken from each with paired-end sequencing.

  Dataset EGAD00001008031

• Transcriptome and Exome from longitudinal samples of human glioblastoma

  We obtained paired longitudinal specimens from a total of 38 glioblastoma (GBM) patients (34 primary and 4 secondary GBM patients). Treatment-naive initial tumors were available for 35 cases; for the other 3 cases, we used the first available recurrent tumors in lieu of initial tumors. Tumor specimens were subjected to whole-exome sequencing (27 of 38 cases, with the matched normal/blood for 22 of the 27 cases) and transcriptome sequencing (30 of 38 cases).

  Dataset EGAD00001001424

• NCT03343197: Clinical Biomarker Data

  Patients with IDH1-mutated low-grade glioma were treated with AG-120 (ivosidenib), AG-881 (vorasidenib), or Placebo for 28 days before surgical resection. A portion of the surgical sample was submitted for exome capture-based transcriptome sequencing (Personalis ACE Whole Transcriptome). Following surgery, subjects had the option to continue (or initiate) treatment with AG-120 or AG-881.This dataset comprises next-generation sequencing data from biopsies obtained in the clinical trial: NCT03343197 (Study of AG-120 and AG-881 in Subjects with Low Grade Glioma).

  Study phs003148

• APOLLO1: Proteogenomic Analysis of Lung Adenocarcinoma

  APOLLO is a proteogenomic study seeking to describe the major genome, transcriptome, proteome and phosphoproteome alterations, subtypes, and molecular predictors of patient outcomes. This study includes 87 lung adenocarcinomas and matched normal tissues from the Lung Cancer Biospecimen Resource Network (https://lungbio.sites.virginia.edu/). Tumor tissues were profiled by whole genome sequencing, transcriptome sequencing, MS-based proteomics and phosphoproteomics, and reverse phase protein arrays. Matched normal tissues were profiled by whole genome sequencing. Clinical and sample data include survival times, patient features, and tumor characteristics.

  Study phs003011

• Evolution of Chronic Lymphocytic Leukemia to Richter's Syndrome (RS)

  Richter's syndrome arising from chronic lymphocytic leukemia is a striking example of an aggressive malignant histology that emerges from indolent cancer. To understand this process, we reconstructed phylogenies based on whole exome sequencing of matched normal, CLL and RS samples. We computationally deconvoluted CLL and RS clones and identified drivers of transformation. We additionally performed whole genome sequencing, whole transcriptome sequencing and single-cell transcriptome sequencing to understand the mutational signatures, genome-wide events and gene expression changes associated with transformation.

  Study phs002458

• APOLLO-OV: Applied Proteogenomics of High Grade Serous Ovarian Carcinoma

  APOLLO is a proteogenomic study seeking to describe the major genome, transcriptome, proteome and phosphoproteome alterations, subtypes, and molecular predictors of patient outcomes. This study includes 70 high grade serous ovarian carcinoma tissues from the Gynecologic Cancer Center of Excellence (https://medschool.usuhs.edu/gso/research/gyn-cancer-center-of-excellence). Bulk and laser microdissection enriched tumor tissues were profiled by whole genome sequencing, transcriptome sequencing, MS-based proteomics and reverse phase protein arrays. Clinical and sample data include survival times, patient features, and tumor characteristics.

  Study phs003488

• Transcriptome Sequencing of Cancer Cell Lines

  In this study we will sequence the transcriptome of Verified Cancer Cell lines. This will be married up to whole exome and whole genome sequencing data to establish a full catalog of the variations and mutations found.

  Dataset EGAD00001000359

• Transcriptome analysis of Treg cells from blood, fat, liver and skin

  Tcells were isolated fom Tissues and FACS sorted. In total 43 samples were processed in 5 replicates with the Takara SmartSeq Stranded kit. Single end fastq-files are supplied.

  Dataset EGAD00001007664

• Whole exome sequencing of 49 tumor-blood pairs and transcriptome sequencing of 44 tumors for adrenocortical tumors

  Adrenal Cushing syndrome, which leads to type 2 diabetes, obesity and hypertension, is caused by ACTH-independent production of glucocorticoid by adrenocortical tumors. To investigate the genetic origins of cortisol-producing adrenocortical tumors, we performed whole exome sequencing of 49 tumor-blood pairs and transcriptome sequencing of 44 tumors

  Study EGAS00001000712

• Whole Transcriptome Analysis + AbSeq + Sample Tag Multiplexing

  Multiomics data for a cohort of 20 COVID-19 patients (10 patients mild, 3 patients moderate, 4 patients severe, 3 patients critical) obtained from peripheral blood mononuclear cells (PBMCs) from longitudinally sampled at hospital admission, discharge, and 1 month thereafter. The data has been obtained a multiwell-based single-cell technology (BD Rhapsody) that includes the analysis of PBMCs' whole transcriptome and a set of 52 surface proteins. The samples of the different patients at different collection times were labelled using a cell hashing strategy with the BD Single-Cell Multiplexing Kit (6 samples for each run).

  Dataset EGAD00001011318

• Uveal Melanoma Immunogenomics Predict Immunotherapy Resistance and Susceptibility

  Immunotherapy using immune checkpoint inhibition (ICI) has shown success in treating metastatic cutaneous melanoma but has limited efficacy against metastatic uveal melanoma (UM), a rare variant arising from the immune privileged eye. To better understand this immune resistance, we performed comprehensive immunogenomic profiling of 100 human UM metastases using clinicogenomics, bulk and single cell transcriptomics, T cell receptor (TCR) repertoire analysis, and tumor infiltrating lymphocyte (TIL) potency assessment. We found that over half of these metastases harbored TIL with potent autologous tumor specificity, despite having low tumor mutational burden and resistance to prior immunotherapies, including ICI and the bispecific T cell engager tebentafusp. These T cell infiltrated metastases displayed activated antigen presenting cells, chronic interferon signaling, and diverse TCR repertoires. However, we observed strikingly low intratumoral TCR clonality and transcriptionally non-proliferative TIL within the tumor microenvironment even after ICI and tebentafusp therapy, demonstrating that these immunotherapies were insufficient to induce proliferation of the tumor reactive TIL. To harness the therapeutic potential of these quiescent TIL, we developed rapid tumor transcriptomic profiling to enable their selective in vivo identification and ex vivo liberation to counter their growth suppression. We demonstrate that adoptive transfer of these transcriptomic selected TIL can promote tumor immunity in patients with metastatic UM when other immunotherapies are incapable.Data that will be available through dbGaP includes raw bulk tumor transcriptomic sequencing data.

  Study phs003330

• Re-Evaluation of Systemic Early Neuromuscular Blockade

  This study of the ROSE trial data explored two distinct molecular subtypes of ARDS (Acute Respiratory Distress Syndrome) to better understand the disease's complexity and potential for personalized treatment. Previous studies had identified different inflammatory profiles in ARDS patients, with this research addressing three key questions: Can these molecular subtypes be consistently identified in a more severe group of ARDS patients? Do these subtypes respond differently to neuromuscular blockade treatment? What specific biological processes differentiate these inflammatory profiles? Advanced transcriptomic and protein analyses examined blood samples from ARDS patients. Analysis of these data revealed two main molecular phenotypes: Hypoinflammatory phenotype (60.4% of patients) Hyperinflammatory phenotype (39.6% of patients) Key findings demonstrated that the hyperinflammatory subtype was associated with:Significantly higher mortality rates relative to hypoinflammatory (61.6% vs. 30.3%)Significantly higher mortality rates relative to hypoinflammatory (61.6% vs. 30.3%)Distinct gene expression patterns related to immune responseUnique changes in genes associated with tissue remodeling and cellular processes Notably, the neuromuscular blockade treatment showed no difference in effects across these subtypes. Complex relationships emerged between gene expression and protein levels, with some genes closely matching their protein counterparts and others displaying more variable connections. The study concludes that these molecular phenotypes possess distinct clinical, protein, and genetic characteristics, suggesting potential for more precise, personalized approaches to ARDS treatment in the future.

  Study phs003929

• Exome and RNA sequencing of relapsed TCF3-PBX1 t(1;19) acute lymphoblastic leukemia

  TCF3-PBX1 (E2A-PBX1) is a recurrent gene fusion in B-cell precursor lymphoblastic leukemia (BCP-ALL), which is caused by the translocation t(1;19)(q23;p13). TCF3-PBX1 BCP-ALL patients typically benefit from chemotherapy; however, many relapse and subsequently develop resistant disease with few effective treatment options. Mechanisms driving disease progression and therapy resistance have not been studied in TCF3-PBX1 BCP-ALL. Here, we aimed to identify novel treatment options for TCF3-PBX1 BCP-ALL by profiling leukemia cells from a relapsed patient, and determine molecular mechanisms underlying disease pathogenesis and progression. By drug sensitivity testing of leukemic blasts from the index patient, control samples and TCF3-PBX1 positive and negative BCP-ALL cell lines, we identified the phosphatidylinositide 3-kinase delta (p110δ) inhibitor idelalisib as an effective treatment for TCF3-PBX1 BCP-ALL. This was further supported by evidence showing TCF3-PBX1 directly regulates expression of PIK3CD, the gene encoding p110δ. Other somatic mutations to TP53 and MTOR, as well as aberrant expression of CXCR4, may influence additional drug sensitivities specific to the index patient and accompanied progression of the disease. Our results suggest that idelalisib is a promising treatment option for patients with TCF3-PBX1 BCP-ALL while other drugs could be useful depending on the genetic context of individual patients.

  Study EGAS00001001876

• Cord blood progenitor CITE-seq dataset

  Sequencing results of single-cell transcriptome and antibody libraries from two biological experiments of cord blood progenitor cells. Four samples from different time points were processed using 10X Genomics Chromium Next GEM Single Cell 3’ Reagent Kits v3.1. Gene expression and antibody-derived libraries were sequenced separately.

  Dataset EGAD50000000405

• CLL PacBio LRTS IsoSeq

  This dataset contains long read transcriptome sequencing of 19 chronic lymphocytic leukemia (CLL) patients with or without mutation in SF3B1, as well as 6 B cell samples from healthy individuals. The BAM files are unaligned CCS reads.

  Dataset EGAD50000000076

• Human inflammatory cardiomyopathies following SARS-CoV2 infection and COVID-19 vaccination dataset

  This dataset consists of transcriptome data of 25 human samples with myocarditis, thereof: 8 without COVID-19, 10 post COVID-19, 4 after COVID-19 vaccination and 3 with MIS-C (Multisystem Inflammatory Syndrome in Children, PIMS).

  Dataset EGAD50000001130

• Single cell multi modal dataset of bone marrow samples from follicular lymphoma patients at diagnosis et one year post treatment

  This dataset contains transcriptome, BCR, TCR and HTO data at the single cell level from follicular lymphoma bone marrow samples at diagnosis (n=19) and one year post rituximab therapy (n=16).

  Dataset EGAD50000001843

• Personalised therapy with MEK inhibition leads to a sustained complete response in an adolescent patient with a recurrent malignant peripheral nerve sheath tumor

  Whole genome sequencing of tumour (90X) - normal (30X) patient pair and bulk transcriptome sequencing (80M PE reads) of tumour sample.

  Dataset EGAD00001006793

• IFNL4 Organoid Transcriptome Profiles

  RNAseq of liver organoids with a dG genotype (B20, nt115, U15) and with a TT genotype (nt5, U16, U19) was performed, which was used to study the impact of IFNλ4 on the cellular response to Sendai viral infection.

  Dataset EGAD00001007820

• Single cell Transcriptome Analysis of regulatory Tcells from blood, fat and skin

  Regulatory Tcells were FACS sorted and processed with 10x Genomics Chromium Next GEM Single Cell 5' v2 sequencing. In total 17 samples were processed. Fastq files are supplied.

  Dataset EGAD00001007665

• miRNA and mRNA transcriptome data

  This dataset contains 278 miRNA and 20 mRNA transcriptomes generated as part of the study "miR-374a-5p regulates inflammatory genes and monocyte function in inflammatory bowel disease."

  Dataset EGAD00001008683

• CTD-ILD BALF and blood scRNA-seq dataset

  CTD-ILD BALF and blood scRNA-seq dataset consists of single-cell transcriptome data of bronchoalveolar lavage fluid (BALF) and blood derived from 30 connective tissue disease-associated interstitial lung disease (CTD-ILD) and 12 idiopathic interstitial pneumonia (IIP) patients.

  Dataset EGAD00001011334

• Longitudinal breast cancer cohort in SMC

  Whole transcriptome sequencing (WTS) of a longitudinal breast cancer (BC) cohort consisting of 146 cases (281 tumors, 109 pairs), including 52 (38%) that achieved pathologic complete responses (pCR) and 85 (62%) that harbored residual diseases at time of surgery.

  Dataset EGAD00001004487

• Childhood B-cell acute lymphoblastic leukemia genomic and transcriptomic data

  The aim of the two studies was: 1) to genetically characterise childhood leukemia patients that lacked established cytogenetic abnormalities (termed B-other leukemia) and assess the clinical features of recurrent genetic abnormalities. 2) Assess the accuracy of whole genome sequencing as a diagnostic genetic test in childhood leukemia, relative to other traditional methods (karyotyping, FISH, MLPA) and whole transcriptome sequencing. As a result, this study includes targeted DNA-sequencing, whole genome sequencing and whole transcriptome sequencing data on childhood leukemia patients enrolled on UK clinical trials (UKALL2003 and UKALL2011).

  Study EGAS00001006863

• Monomorphic sarcomas RNAseq dataset

  Dataset is composed of FASTQ files from 165 samples of small round cell sarcomas which were RNA-sequenced (whole transcriptome) with either Illumina HiSeq 2500 (120 million reads per sample, paired-end 100 pb) or Illumina NextSeq 500 (110 million reads per sample, paired-end 150)

  Dataset EGAD00001003121

• The Transcriptome of PLX4032 resistance

  We have collected material from a patient who had BrafV600E mutant melanoma that was treated with PLX4032. We have germline DNA from the patient and DNA and RNA from distinct lesions before and after treatment with PLX4032. We have transcriptome sequenced these samples to obtain a snap shot of the mechanisms of resistance that are operative.

  Dataset EGAD00001000599

• Reconstruction of human terminal erythroid differentiation cell at single cell level

  Terminal erythroid differentiation cells(GYPA+ cells) were isolated from neonate cord blood(CB) and adult bowe marrow(BM). single cell transcriptome sequencing library was constructed by 10X genomics system and sequenced by Illumina X ten platform. Sequencing data was analyzed to profile dynamic expression genes and centre regulators during terminal erythroid differentiation stage within CB and BM.

  Study EGAS00001003114

• Beta cell transcriptome UNIGE

  Dac EGAC00001000101

• 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

• DAC Human Skeletal Muscles Transcriptome

  Dac EGAC00001002603

• MSI-Exome-Transcriptome-DAC

  Dac EGAC00001001845

• Whole Exome and Transcriptome Sequencing in Sporadic ALS

  Amyotrophic lateral sclerosis (ALS), also known as Lou Gehrig's disease, is a fatal and devastating neurodegenerative disorder that causes the progressive death of upper and lower motor neurons. Although many efforts have been done to elucidate molecular factors involved in the onset and progression of the disorder, the causes of ALS are yet unknown and undefined. Transcriptome studies, based mostly on microarrays, have revealed multiple perturbations of the motor neuron function, supporting the current idea that several cellular events contribute to the pathobiology of the disease, including mitochondrial dysfunction, enhanced apoptosis, glutamate-mediated excitotoxicity, free radical injury, protein misfolding, abnormal calcium metabolism and altered axonal transport. In the present study, we have deeply sequenced the whole transcriptome of ventral horns of the human lumbar spinal cord from matched control and ALS post-mortem donors. Whole exome sequencing from the same donors has also been performed to exclude known genetic variants associated to the familiar form of ALS. In addition, to characterize the ALS transcriptome we have sequenced the RNA fraction at low molecular weight in the same tissues and individuals. Genomic and transcriptomic reads have been generated using the Illumina HiSeq2000 sequencer.

  Study phs000747

• A Single Cell Atlas of Gene Regulatory Elements in the Human Heart

  Background: Cis-regulatory elements such as enhancers and promoters are crucial for directing gene expression in the human heart. Dysregulation of these elements can result in many cardiovascular diseases that are major leading causes of morbidity and mortality worldwide. In addition, genetic variants associated with cardiovascular disease risk are enriched within cis-regulatory elements. However, the location and activity of these cis-regulatory elements in individual cardiac cell types remains to be fully defined. Methods: We performed single nucleus ATAC-seq and single nucleus RNA-seq to define a comprehensive catalogue of candidate cis-regulatory elements (cCREs) and gene expression patterns for the distinct cell types comprising each chamber of four non-failing human hearts. We used this catalogue to computationally deconvolute dynamic enhancers in failing hearts and to assign cardiovascular disease risk variants to cCREs in individual cardiac cell types. Finally, we applied reporter assays, genome editing, and electrophysiogical measurements in in vitro differentiated human cardiomyocytes to validate the molecular mechanisms of cardiovascular disease risk variants. Results: We defined >287,000 candidate cis-regulatory elements (cCREs) in human hearts at single-cell resolution, which notably revealed gene regulatory programs controlling specific cell types in a cardiac region/structure-dependent manner and during heart failure. We further report enrichment of cardiovascular disease risk variants in cCREs of distinct cardiac cell types, including a strong enrichment of atrial fibrillation variants in cardiomyocyte cCREs, and reveal 38 candidate causal atrial fibrillation variants localized to cardiomyocyte cCREs. Two such risk variants residing within a cardiomyocyte-specific cCRE at the KCNH2/HERG locus resulted in reduced enhancer activity compared to the non-risk allele. Finally, we found that deletion of the cCRE containing these variants decreased KCNH2 expression and prolonged action potential repolarization in an enhancer dosage-dependent manner. Conclusion: This comprehensive atlas of human cardiac cCREs provides the foundation for not only illuminating cell type-specific gene regulatory programs controlling human hearts during health and disease, but also interpreting genetic risk loci for a wide spectrum of cardiovascular diseases.

  Study phs002204

• Longitudinal Studies of Patients with Familial Platelet Disorder with Associated Myeloid Malignancy (FPDMM)

  FPDMM (OMIM #601399) is a rare autosomal dominant disease characterized by defective megakaryocytic development, thrombocytopenia, platelet functional defects, and a life-long risk of developing hematological malignancies. FPDMM is caused by germline mutations in the RUNX1 gene, which encodes a master regulator of hematopoiesis. The overall lifetime risk of hematological malignancies in FPDMM patients is 35 - 45%. It is hypothesized that mutations in other genes cooperate with the germline RUNX1 mutations for leukemia development. However, it is not clear which genes need to be mutated for leukemia to develop and which biomarkers or clinical tests can be used to predict which patients will progress to leukemia. Likewise, there are no treatments and/or preventative measures that can reduce or stop disease progression except for stem cell transplantation, which is not available for all patients and may be associated with significant complications. To address these questions, we launched a longitudinal natural history study of patients associated with RUNX1 germline mutations at the NIH Clinical Center in early 2019 (Trial Registration ID: NCT03854318). The goals of this study are to: (1) perform comprehensive longitudinal phenotyping of FPDMM patients to document the full spectrum of both hematopoietic and non-hematopoietic manifestations of the disease; and (2) perform extensive genomic analyses of FPDMM patient samples to identify cooperating genomic variants, which may confer growth advantage that leads to clonal expansion of affected hematopoietic cells that may serve as the precursor to malignancies. The data available through dbGaP include exome sequencing and RNA-seq data from these patients. Diverse germline mutation types were identified in the RUNX1 gene, including splice site mutations and large deletions, in addition to nucleotide substitutions and small indels. Somatic mutations, especially in genes associated with clonal hematopoiesis of indeterminate potential (CHIP), were found in a substantial proportion of FPDMM patients who were leukemia-free. The findings suggest that the genomes in these patients are prone to somatic mutations and monitoring the dynamic changes of these somatic mutations prospectively may provide a way to predict progression to malignancies.

  Study phs003075

• Evolution of Chromatin Architecture and Transcriptional Regulation in Mammals

  Changes in gene expression are a critical force driving the evolution of form and function. As a result, the mechanisms by which gene expression evolves have become a subject of intense interest. A number of investigators have measured evolutionary changes in gene expression at the chromatin, mRNA, and protein levels, leading to new insights about how species evolve. However, studies of different stages in gene expression have not always been in agreement. For example, the extremely rapid rates of evolutionary changes that have been widely observed at enhancers appear to conflict with the slower rates observed in mRNA abundance. We recently completed a major comparative study in primates showing that this disparity between enhancer and mRNA evolution, in part, reflects extensive compensation at enhancers that jointly determine transcription at target genes. Likewise, related findings have demonstrated that post-transcriptional changes buffer protein abundance to relatively more common differences in mRNA expression. Together, these recent findings demonstrate that evolutionary changes affecting multiple stages of transcriptional regulation often have interdependent effects on gene expression. Here we propose to determine how stages early during transcriptional regulation work in concert, either to conserve gene expression through compensatory changes across stages, or, in rare cases, to change mRNA in ways that alter organism phenotypes. Our central hypothesis is that interactions between stages are common, especially at long evolutionary time-scales. To test this hypothesis we propose an ambitious plan to collect rich genomic data profiling distinct stages of gene expression in two cell types and three tissues from nine mammalian species. We have focused our study on several early rate-limiting steps in mRNA production, using molecular assays selected to provide orthogonal sources of information about chromatin architecture (Hi-C/Hi-ChIP), accessibility (ATAC-seq), transcription (PRO-seq), and mRNA levels (RNA-seq). This project will produce the largest resource of genomic data uniformly collected across mammals to date. We will integrate genomic data using a suite of new computational tools, which together will provide a new understanding of how distinct regulatory stages work in concert during regulatory evolution.

  Study phs002146

• Childhood Cancer Data Initiative (CCDI): Molecular Characterization across Pediatric Brain Tumors and Other Solid and Hematologic Malignancies for Research, Diagnostic, and Precision Medicine

  This study contains tumor and germline WGS, RNA-Seq, Clinical Panel Sequencing, and other omics and molecular data for patients with pediatric brain tumors and other solid and hematologic malignancies. This data has been collected from multiple organizations including the multi-institute Children's Brain Tumor Network (CBTN), the Pacific Pediatric Neuro-Oncology Consortium (PNOC), and the Children's Hospital of Philadelphia Division for Genomic Diagnostics (CHOP DGD). In addition to being available pre-publication and without embargo via dbGaP and the NCI Cancer Research Data Commons, this data is made available via Cavatica, PedcBioPortal and the Kids First Data Resource Portal. Collectively, this availability strives to accelerate the research process and enable members of the scientific and patient communities to partner and make discoveries faster than ever before.In 2019, the CBTN launched the Pediatric Brain Tumor Atlas, which now comprises the largest collection of childhood brain tumor data in the world. This resource is helping accelerate not only brain tumor research, but is also empowering discovery for other rare childhood conditions. Brain tumors are the most common form of cancer in children aged 0-19 in the United States, and are the largest cause of cancer-related deaths. The estimated number of new cases in 2019 is nearly 3,800, and thus brain tumors are a rare disease. Despite their relative rarity, the years of potential life lost due to brain tumors in 2009 was estimated at 47,631 years for children and adolescents aged 0-19 in the United States; this is a disproportionate amount of life lost compared to adult cancers and represents an unrecognized societal threat. There is an urgent need to improve therapies for these children. This sequencing cohort defines the largest, clinically annotated pediatric brain tumor cohort study to date and seeks to define the intersection of germline and somatic underpinnings of pediatric brain tumors across a shared developmental context of cancer and structural birth defects.

  Study phs002517

• NextGen Consortium: The iPSCORE (iPSC Collection for Omic Research) Resource for Studying the Impact of Genetic Variation on Molecular Phenotypes

  The iPSC Collection for Omic Research (iPSCORE) Resource was created as part of the Next-Gen Consortium funded by NHLBI. The overarching purpose of the resource is to provide a large collection of human induced pluripotent stem cells (iPSCs) for use in studying the impact of genetic variation on molecular and physiological phenotypes. The resource has been used in a number of studies in the Dr. Kelly A. Frazer's Lab examining both the characteristics of human iPSCs and a variety of iPSC-derived cell types including cardiovascular progenitor cells (iPSC-CVPCs), pancreatic precursor cells (iPSC-PPCs), and retina pigment epithelium cells (iPSC-RPEs). We have shown that the iPSCs, CVPCs, and PPCs are suitable surrogate models to identify genetic factors active in early developmental processes because they exhibit fetal-like molecular properties. A total of 273 individuals have participated in the study, of which 222 have had iPSCs generated from fibroblasts. Of the 273 individuals, 181 are part of 55 families that include 24 monozygotic twin pairs and 5 dizygotic twin pairs, allowing for the incorporation of familial relationships into genetic analyses. Germline DNA has been sequenced from blood or fibroblast samples for all 273 individuals (available through dbGaP phs001325) and other genomic data (RNA-seq, DNA methylation, genotype arrays, ATAC-seq, H3K27ac ChIP-seq, HiC-seq) have been generated from the 222 iPSCs as well as derived cell types (available through dbGaP phs000924). QTL analyses were conducted for multiple omics data types and summary statistics are available through dbGaP phs0001325. Important note: Of the 273 individuals, 268 are consented for general research use and 5 are consented for cardiac research only. For detailed information about iPSCORE Collection including samples, methods used to generate the data, and how to access the datasets visit the Frazer lab website.The 222 well characterized iPSC lines that constitute the iPSCORE resource are available, please contact Dr. Kelly A. Frazer (kafrazer@health.ucsd.edu) if you are interested in obtaining the collection.

  Study phs000924

• NextGen Consortium: The iPSCORE (iPSC Collection for Omic Research) Resource for Studying the Impact of Genetic Variation on Molecular and Physiological Phenotypes - Whole Genome Sequence

  The iPSC Collection for Omic Research (iPSCORE) Resource was created as part of the Next-Gen Consortium funded by NHLBI. The overarching purpose of the resource is to provide a large collection of human induced pluripotent stem cells (iPSCs) for use in studying the impact of genetic variation on molecular and physiological phenotypes. The resource has been used in a number of studies in the Dr. Kelly A. Frazer's Lab examining both the characteristics of human iPSCs and a variety of iPSC-derived cell types including cardiovascular progenitor cells (iPSC-CVPCs), pancreatic precursor cells (iPSC-PPCs), and retina pigment epithelium cells (iPSC-RPEs). We have shown that the iPSCs, CVPCs, and PPCs are suitable surrogate models to identify genetic factors active in early developmental processes because they exhibit fetal-like molecular properties.A total of 273 individuals have participated in the study, of which 222 have had iPSCs generated from fibroblasts. Of the 273 individuals, 181 are part of 55 families that include 24 monozygotic twin pairs and 5 dizygotic twin pairs, allowing for the incorporation of familial relationships into genetic analyses.Germline DNA has been sequenced from blood or fibroblast samples for all 273 individuals (available through dbGaP phs001325) and other genomic data (RNA-seq, DNA methylation, genotype arrays, ATAC-seq, H3K27ac ChIP-seq, HiC-seq) have been generated from the 222 iPSCs as well as derived cell types (available through dbGaP phs000924).QTL analyses were conducted for multiple omics data types and summary statistics are available through dbGaP phs0001325.Important note: Of the 273 individuals, 268 are consented for general research use and 5 are consented for cardiac research only.For detailed information about iPSCORE Collection including samples, methods used to generate the data, and how to access the datasets visit the Frazer lab website.The 222 well characterized iPSC lines that constitute the iPSCORE resource are available, please contact Dr. Kelly A. Frazer (kafrazer@health.ucsd.edu) if you are interested in obtaining the collection.

  Study phs001325

• B cell receptor silencing reveals origin and dependencies of high-grade B cell lymphomas with MYC and BCL2 rearrangements

  High-grade B cell lymphomas with MYC and BCL2 rearrangements (HGBCL-DH-BCL2) represent highly aggressive Germinal center (GC) derived B cell malignancies with dismal prognosis and limited therapeutic options. In the present study, we investigated the expression of BCR complex components, including immunoglobulin (IG) heavy (H) and light (L) chains, and CD79A and CD79B signaling subunits in HGBCL-DH-BCL2, scoring 65% of cases with undetectable IGH immunoreactivity (IGHUND). Transcriptomics (bulk RNA-seq) and genetic (whole exome/genome sequencing) analyses indicated that IGHUND and IGH+ HGBCL-DH-BCL2 lymphomas represent distinct biological entities. Specifically, IGHUND HGBCL-DH-BCL2 exhibit a GC DZ-like molecular program, and select subset-specific gene mutations pointing to distinct evolutionary trajectories respect to the IGH+ counterparts. IG profiling revealed that IGHUND HGBCL-DH-BCL2 preserved potentially productive, hypermutated IGH variable (V) gene rearrangements, indicating a selective advantage conferred to the malignant B cells by residual IGH molecules. Accordingly, disruption of the productively rearranged IGHG1 gene in BCRnull HGBCL-DH-BCL2 cell line model confirmed the dependency on IGH expression for optimal fitness. Using transcriptomics and in situ RNA-scope analysis, we reported that IGHUND HGBCL-DH-BCL2 originated from IG-class switched GC B cells, while IGH-expressing tumors were selected for continuous IGM expression. Moreover, while IGH+ HGBCL-DH-BCL2 favor IGM/IG-Kappa expression, IGHUND counterparts complete IG-Lambda light chain rearrangements. Notably, BCR silencing, caused by accelerated IGH turnover and reduced IGH expression, precedes HGBCL-DH-BCL2 onset, inducing RAG1/2-dependent IG light chain editing and eventually facilitating t(8;22)/IGL::MYC translocations. Finally, IGH silencing observed in HGBCL-DH-BCL2 cell models, which leads to intracellular retention/silencing of CD79B, results in reduced sensitivity to the CD79B-targeting antibody-drug conjugate Polatuzumab-vedotin. Collectively, HGBCL-DH-BCL2 originates from isotype-switched t(14;18)+ GC B cells that undergo IG light chain editing fuelling intra-clonal diversification, BCR silencing, and the acquisition of t(8;22) translocation, while preserving IGH dependency.

  Study EGAS50000001047

• METSIM (METabolic Syndrome In Men) Study

  The METSIM Study includes 10,197 men, aged from 45 to 73 years, randomly selected from the population register of the town of Kuopio, Eastern Finland, and examined in 2005-2010. The aim of the study is to investigate genetic and non-genetic factors associated with the risk of type 2 diabetes (T2D), cardiovascular disease (CVD), and insulin resistance-related traits in a cross-sectional and longitudinal setting. Study protocol includes collection of data on CVD risk factors (smoking, exercise, diet, history of chronic diseases including coronary heart disease, stroke, cardiac failure, medication, history of diabetes or early onset coronary heart disease in the family), questionnaire on the FINDRISC Score, measurement of height, weight, waist, hip, blood pressure, and bioimpedance for the evaluation of fat percentage. July 2016 - The first study release (v1) included phenotype and whole exome sequencing (WES) data of n=982 participants in substudy: Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Project 1: Metabolic Syndrome in Men Study (METSIM) - phs001100.v2.p1. The second study release (v2) included phenotype data for the entire METSIM cohort and made two additional substudies available, phs000919.v1.p1 and phs000752.v1.p1. The third study release (v3) made three subcutaneous adipose biopsy substudies available, phs003385.v1.p1, phs003386.v1.p1, and phs003387.v1.p1.The fourth study release (v4) added phenotype data for the subcutaneous adipose biopsies, made two additional substudies available, phs01579.v1.p1 and phs004033.v1.p1, and 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" section of this top-level study page phs000743 METSIM Study. phs000752 METSIM FinMetSeq Exome Sequencing phs000919 METSIM GWAS and Exome Chip phs001100 METSIM T2D-GENES Exome Sequencingphs001579 METSIM CCDG Whole Genome Sequencingphs003385 METSIM Subcutaneous Adipose Needle Biopsy RNA-Seq phs003386 METSIM Subcutaneous Adipose Needle Biopsy ATAC-Seq phs003387 METSIM Subcutaneous Adipose Surgical Biopsy RNA-Seqphs004033 METSIM Metabolomics

  Study phs000743

• Etiology of congenital thyroid dysfunction in Down Syndrome: a multi-omics investigation

  The goal of this study was to investigate dfiferences in the thyroid DNA methylome and transcriptome between fetuses with Down syndrome and fetuses with no genetic/developmental abnormality.

  Study EGAS50000000264

• Spatial and temporal transcriptome analysis on human skeletal muscle regeneration

  Skeletal muscle carries a unique ability for adaptation as well as regeneration that highly depends on a supportive cellular microenvironment. Here we show that spatial and single-cell transcriptomic analysis in human skeletal muscle is a unique approach to illuminate cellular interactions in the microenvironment.

  Dataset EGAD50000000263

• Effect_of_FAM50_knockout_on_the_transcriptome

  A knockout clone has been generated for both FAM50A and FAM50B; knockout of the other gene is then performed and the transcriptome is analysed to look at the effect of dual gene loss.

  Study EGAS00001004836

• STAT1 AM RNAseq

  The transcriptome of peripheral blood cells (PBMCs) from control or patients with an activation mutation on the STAT1 gene was analyzed. This analysis aimed to identify the major changes in the circulating immune cells of patients with STAT1 mutation and compare this with the result of the perturbation prediction tool huva (human variation, R).

  Dataset EGAD00001006962

• Whole transcriptome sequencing of the dMMR colorectal cancer cohort

  We leveraged the ImmunoID NeXT platform, an Immune-enhanced multiomics platform to profile a cohort of patients with dMMR CRC. This sub-study includes the whole transriptome sequencing data

  Study EGAS50000001742

• CTD-ILD_BALF_and_blood_scRNA-seq_data

  Study EGAS00001007539

• A prospective pilot study of genome-wide exome and transcriptome profiling in patients with small cell lung cancer progressing after first-line therapy

  In this prospective study, custom genome-wide exome and whole transcriptome sequencing (NGS) was used to identify genomic events and associated expression changes in advanced Small Cell Lung Cancer (SCLC) and attempt to prescribe systemic therapy based on the results. Tumor/normal pairs were sequenced from 12 patients with advanced SCLC for this study.

  Study phs001366

• POT1_splice_site_mutant_analysis

  We are interested in the contribution mutations in the Shelterin complex protein POT1 may have to the development of melanoma. We have identified a patient who carries a splice site mutation in POT1 and as part of our analysis of this gene we aim to sequence the transcriptome of this patient to see how this mutation influences splicing. RNA has been obtained from lymphocytes collected from the patient.

  Study EGAS00001000571

• Whole transcriptome and exome sequencing of childhood ALL

  Gene fusion is a major class of genomic abnormalities in childhood acute lymphoblastic leukemia (ALL) and sentinel chromosomal rearrangements involving EP300 and CREBBP may cause global epigenetic deregulation during leukemogenesis with potentials for therapeutic targeting. This dataset includes whole transcriptome sequencing of 231 children with acute lymphoblastic leukemia from a Singapore-Malaysia frontline clinical treatment protocol.

  Study EGAS00001001858

• Adult B-precursor acute lymphoblastic leukemia RoCK and ROI single-cell transcriptome

  Whohle Transcriptome sequencing was performed following the manufactures protocol from BD Rhapsody. Capture of BCR::ABL1 was performed using RoCK and ROI. RoCK and ROI is based on barcoded beads of the BD Rhapsody platform. For RoCKseq specific capture, TSO oligos on BD Rhapsody beads are modified with a/ multiple capture sequence(s) specific to transcripts of interest. ROIseq, on the other hand, is based on specific primers which are spiked in during library generation, directing reads to regions of interest (ROIs). Multiple scRNAseq experiments were performed on several biological samples to validate RoCK and ROI.

  Study EGAS50000001366

• CBB/SAGSC transcriptome-genome data access committee

  Dac EGAC00001001919

• Breast cancer sequencing data

  Study EGAS00001007336

• Microarray Markers of Response

  Study EGAS00001005477

• BCL11B Enhancer Hijacking by t(14;16)(q32;q24) Translocation Defines a Novel High-Risk Subtype of T-ALL

  We performed integrated analysis of pediatric and adult T-ALL and mixed phenotype acute leukemias (MPALs) by whole-genome and whole-transcriptome sequencing.

  Study EGAS50000001254

• DCIS_FF_RNAseq

  This RNAseq dataset contains full transcriptome data on n=77 pure DCIS samples. The RNA is derived from fresh-frozen DCIS samples, obtained from two hospital based cohorts (NKI cohort and Oslo cohort). The libraries were sequenced with 54 bp paired end reads using a Novaseq instrument (Illumina). We share fastq data files of paired end sequencing (two files per sample).

  Dataset EGAD50000002123

• Dual spatially resolved transcriptomics for human host-pathogen colocalization studies in FFPE tissue sections

  Advamced Visium Spatial Gene Expression assay for FFPE tissues with human and SARS-CoV-2 whole transcriptome (WT) information at a 55 µm resolution. The dataset consists of 13 tissue sections from 5 patient lung tissue samples, 3 from COVID-19 patients and 2 from control patients.

  Dataset EGAD00001008701

• RNA-Seq of PBMC's from rUTI Patients and Healthy Controls

  Recurrent urinary tract infections (rUTIs) are a major health burden worldwide, with history of infection being a significant risk factor. While the gut is a known reservoir for uropathogenic bacteria, the role of the microbiota in rUTI remains unclear. We conducted a year-long study of women with and without history of rUTIs, from whom we collected urine, blood and monthly fecal samples for multi-omic interrogation. The rUTI gut microbiome was significantly depleted in microbial richness and butyrate-producing bacteria compared to controls, reminiscent of other inflammatory conditions, though Escherichia coli gut and bladder dynamics were comparable between cohorts. Blood samples revealed signals of differential systemic immunity, leading us to hypothesize that rUTI susceptibility is in part mediated through a syndrome involving the gut-bladder axis, comprising gut dysbiosis and differential immune response to bacterial bladder colonization, manifesting in symptoms. This work highlights the potential for microbiome therapeutics to prevent and treat rUTIs.  (Reprinted from medrxiv.org ) 

  Study phs002728

• Neoadjuvant nivolumab or nivolumab plus ipilimumab in early-stage triple negative breast cancer: phase 2 adaptive BELLINI trial. RNA-Seq

  The adaptive BELLINI trial explored whether short combination ICI induces immune activation (primary endpoint: two-fold increase in CD8+ T cells or IFNG), providing rationale for neoadjuvant ICI without chemotherapy. In window of opportunity cohorts A (4 weeks anti-PD1) and B (4 weeks anti-PD1 + anti-CTLA4), we observed immune activation in 53% (8/15) and 60% (9/15) of patients, respectively. High tumor-infiltrating lymphocytes (TILs) correlated with response. Based on these data, we opened cohort C for patients with high TILs (≥50%) who received 6 weeks neoadjuvant anti-PD1 + anti-CTLA4 followed by surgery (primary endpoint: pathological complete response, pCR). 53% (8/15) of patients had major pathological response (< 10% viable tumor) at resection, with 33% (5/15) having pCR. All cohorts met Simon’s two-stage threshold for expansion to stage II. In conclusion, neoadjuvant immunotherapy without chemotherapy demonstrates potential efficacy and warrants further investigation in patients with early TNBC.

  Study EGAS50000000567

• Rna-Seq Leiomyosarcoma subtypes

  Leiomyosarcomas (LMS) are genetically heterogeneous tumors differentiating along smooth muscle lines. Currently, LMS treatment is not informed by molecular subtyping and is associated with highly variable survival. While disease site continues to dictate clinical management, the contribution of genetic factors to LMS subtype, origins, and timing are unknown. Here we analyzed 70 genomes and 130 transcriptomes of LMS, including multiple tumor regions and paired metastases. Molecular profiling highlighted the extremely early origins of LMS. Three specific subtypes of LMS develop from distinct lineages of smooth muscle cells. Of these, dedifferentiated LMS with high immune infiltration and tumors primarily of gynaecological origin acquired the highest burden of genomic mutation and are associated with worse survival. Homologous recombination defects lead to genome-wide mutational signatures, and a corresponding sensitivity to PARP and other DNA damage response inhibitors, suggesting a novel therapeutic strategy for LMS. Finally, by phylogenetic reconstruction, we present evidence that clones seeding lethal metastases arise decades prior to LMS diagnosis.

  Study EGAS00001004783

• Single-cell RNA-seq of immune cells sorted from human melanoma tumors

  Tumor immune cell compositions play a major role in response to immunotherapy but the heterogeneity and dynamics of immune infiltrates in human cancer lesions remain poorly characterized. Here we identify conserved intratumoral CD4 and CD8 T cell behaviors in scRNA-seq data from 25 melanoma patients. We discover a large population of CD8 T cells showing continuous progression from an early effector "transitional" into a dysfunctional T cell state. CD8 T cells that express a complete cytotoxic gene set are rare, and TCR sharing data suggest their independence from the transitional and dysfunctional cell states. Notably, we demonstrate that dysfunctional T cells are the major intratumoral proliferating immune cell compartment and that the intensity of the dysfunctional signature is associated with tumor-reactivity. Our data demonstrate that CD8 T cells previously defined as exhausted, are in fact a highly proliferating, clonal and dynamically differentiating cell population within the human tumor microenvironment.

  Study EGAS00001003363

• Comparison of 3 protocols for deriving pancreatic progenitors from hPSC with RNA-seq and ATAC-seq

  Several distinct differentiation protocols for deriving pancreatic progenitors (PP) from human pluripotent stem cells have been described but it remains to be shown how similar the PP are across protocols, and how well they resemble their in vivo counterparts. Here we evaluated three differentiation protocols; performed RNA and ATAC-seq on isolated PP derived with these, and compared them to fetal human pancreas populations. This enabled us to define a shared transcriptional and epigenomic signature of the PP, including several genes not previously implicated in pancreas development. Furthermore, we identified a significant and previously unappreciated cross-protocol variation of the PP through multi-omics analysis and demonstrate how such information can be applied to refine differentiation protocols for derivation of insulin-producing beta-like cells. Together, our study highlights the importance of a detailed characterization of defined cell populations derived from distinct differentiation protocols, and provides a valuable resource for exploring human pancreatic development.

  Study EGAS00001003513

• Super enhancers define regulatory subtypes and cell identity in neuroblastoma - RNA-seq

  Half of the children diagnosed with neuroblastoma have high-risk disease, disproportionately contributing to overall childhood cancer-related deaths. In addition to recurrent gene mutations, there is increasing evidence supporting the role of epigenetic deregulation in disease pathogenesis. Yet, comprehensive cis-regulatory network descriptions from neuroblastoma tissues are lacking. Here, using genome-wide H3K27ac profiles across 60 neuroblastomas, covering the different clinical and molecular subtypes, we identified four major super enhancer-driven epigenetic subtypes and their underlying master regulatory networks. Three of these subtypes recapitulated known clinical groups, namely MYCN amplified, MYCN non-amplified high-risk and MYCN non-amplified low-risk neuroblastomas. The fourth subtype, exhibiting mesenchymal characteristics, shared features with multipotent Schwann cell precursors, was induced by RAS activation and enriched in relapsed disease. Notably, CCND1, a disease essential gene, was regulated by both mesenchymal and adrenergic regulatory networks converging on distinct super-enhancer modules. Together, this reveals subtype-specific super-enhancer regulation in neuroblastoma.

  Study EGAS00001004552

• RNA-seq from human embryonic tissues (additional samples 2018)

  How the genome activates or silences transcriptional programmes governs organ formation. Little is known about this in human post-implantation embryos undermining our ability to benchmark the fidelity of in vitro stem cell differentiation or cell programming, or interpret noncoding variation as potential causes of disease. Here, by studying histone modification we identified genome-wide open chromatin states and active repression across thirteen tissues during human organogenesis. We integrated the data with transcription to build the first view of how promoter states from nearly 20,000 genes differentially regulate alternative organ fates, arguing against bivalency during human organogenesis. The data illustrate tissue-specific as well as complex patterns of enhancer activity functional in zebrafish and impute master transcription factors. Overlaying 739 noncoding de novo mutations in patients allowed phenotypic correlation of developmental disorders to unanticipated target genes. Taken together, the data provide a comprehensive genomic framework for understanding normal and abnormal human development.

  Study EGAS00001003738

• Single-cell RNA-seq of bronchoalveolar lavage (BAL) fluid of late stage severe COVID-19 patients

  COVID-19-induced ‘acute respiratory distress syndrome’ (ARDS) is associated with prolonged respiratory failure and high mortality, but the mechanistic basis of lung injury remains incompletely understood. Here, we analyzed pulmonary immune responses and lung pathology in two cohorts of patients with COVID-19 ARDS using functional single cell genomics, immunohistology and electron microscopy. We describe an accumulation of CD163-expressing monocyte-derived macrophages, that acquired a profibrotic transcriptional phenotype during COVID-19 ARDS. Gene set enrichment and computational data integration revealed a significant similarity between COVID-19-associated macrophages and profibrotic macrophage populations identified in idiopathic pulmonary fibrosis. COVID-19 ARDS was associated with clinical, radiographic, histopathological, and ultrastructural hallmarks of pulmonary fibrosis. Exposure of human monocytes to SARS-CoV-2, but not Influenza A virus or viral RNA analogs, was sufficient to induce a similar profibrotic phenotype in vitro. In conclusion, we demonstrate that SARS-CoV-2 triggers profibrotic macrophage responses and pronounced fibroproliferative ARDS.

  Study EGAS00001005634

• RNA-seq on patient-derived, stage II, CRC cell lines

  The gut microbiome is a key player in the immunomodulatory and pro-tumorigenic microenvironment in colorectal cancer (CRC). It is well established that Fusobacterium’s virulence factors are responsible for its pro-tumorigenic properties, however the role of its metabolic cross-talk with the tumor remains unexplored. Here we use in vitro, in vivo, and in silico methods to describe a novel microbe-host interaction keystone: formate. Omics data reveals molecular signatures, linking a metabolically driven CRC phenotype with Fusobacteria. We observed a metabolic shift towards increased F. nucleatum formate secretion in gut-on-chip model co-cultures with patient-derived CRC cells, along with an accelerated cancer glutamine metabolism. We show that high formate levels trigger AhR signaling, increase cancer stemness and cellular invasion. Finally, we observed an expansion of Th17 cells accompanying F. nucleatum-induced tumorigenesis. Moving beyond observational studies, we applied new experimental approaches for gaining ecosystem-level mechanistic understanding of F. nucleatum’s role in cancer pathogenesis.

  Study EGAS00001005948

• Single-cell RNA-seq and spatial transcriptomics data for the sarcoidosis baseline project

  Granulomas are lumps of immune cells that can form in various organs. Most granulomas appear unstructured, yet they have some resemblance to lymphoid organ formation. To better understand granuloma formation, we performed single-cell sequencing and spatial transcriptomics on granulomas from patients with sarcoidosis and bioinformatically reconstructed the underlying gene-regulatory networks. We discovered an immune stimulatory environment in granulomas that repurposed transcriptional programs associated with lymphoid organ development. Granuloma formation followed characteristic spatial patterns and involved genes linked to immunometabolism, cytokine and chemokine signaling, and extracellular matrix remodeling. Three cell types emerged as key players in granuloma formation: metabolically reprogrammed macrophages, cytokine-producing Th17.1 cells, and fibroblasts with inflammatory and tissue remodeling phenotypes. Pharmacological inhibition of one of the identified processes attenuated granuloma formation in a sarcoidosis mouse model. We show that human granulomas adopt characteristic aspects of normal lymphoid organ development in aberrant combinations, indicating that granulomas constitute aberrant lymphoid organs.

  Study EGAS00001006970

• Determination of cell specific regulatory enhancers in hematopoetic models

  The BLUEPRINT project is a large-scale project investigating epigenetic mechanisms involved in blood formation, in health and disease. The human variation workpackage (WP10, led by NS) of the project seeks to characterize the effect of common sequence variation on the epigenome status of a cell. To do this, the project will use highly purified blood cells to minimise "experimental noise" and therefore enhance the power to discover modest effects. Two peripheral blood cell types, the CD14+CD16- monocyte (an important central orchestrator of adaptive immunity and a bridge between innate and adaptive immunity) and the CD65+CD9- neutrophilic granulocyte (the frontline cell for innate immunity) have been selected for this purpose. The two types of cells will be obtained at high purity from adult blood (AB) of 200 healthy males and females, respectively. Cells will be purified by using already validated and fully operational protocols that are based on density gradient centrifugation of the buffy coat obtained from whole blood, followed by magnetic bead-based purification using monoclonal antibodies against Cluster of Differentiation (CD) lineage-specific cell surface markers. Units of 475 ml of AB will be obtained from consenting volunteers of the Cambridge BioResource (CBR), a panel of 10,000 healthy volunteers local to Cambridge who have already consented to participate in biomedical research and of whom biological samples (DNA, plasma, serum) and lifestyle data have been deposited in a repository and database, respectively. We are requesting funding from the Human Diversity project to sequence the genomes of the 200 CBR volunteers at low pass (6x coverage). Nuclei, DNA and RNA will be recovered from the purified cells and made available for RNA-seq, DNA-seq and ChIP-seq and genomic DNA for entire genome sequencing will be recovered from the DNA repository.

  Dataset EGAD00001002205

• Weill Cornell Medicine Human Breast Transcriptome Study Commitee

  Dac EGAC00001001739

• Circadian Clock Properties of T2D Patients

  Study EGAS00001003622

• DAC for study Hypothalamic transcriptome in Prader-Willi syndrome

  Dac EGAC00001000869

• Fibromyalgia versus small fiber neuropathy: Diverse keratinocyte transcriptome signature

  Dac EGAC00001001934

• Genomic and transcriptome analysis for intrahepatic cholangiocarcinoma

  Study EGAS00001006007

• METR-GT: Manchester Eye Tissue Repository - Genome Transcriptome resource

  Dac EGAC50000000807

• Transcriptome and epigenome characterization of BMP signaling effects on H3.3K27M DIPG

  We profiled transcriptome and epigenome of BMP signaling effects on H3.3K27M DIPG.

  Dataset EGAD00001007768

• Human Skeletal Muscles Transcriptome

  We generated a large transcriptome atlas of human skeletal muscles by collecting biopsies from 6 different muscles to determine molecular signatures that may be distinct between leg muscles. The biopsies were collected from gracilis (GR), semitendinosus (ST), vastus lateralis (VL), vastus medialis (VM), rectus femoris (RF), and gastrocnemius lateralis (GL) muscles. We also investigated molecular differences within the muscle by including two biopsies from the middle and distal sides of the semitendinosus muscle (STM and STD, respectively). In total, 128 samples from 20 individuals (aged 25 ± 3.6 yr) were analyzed.

  Dataset EGAD00001008657

• Whole transcriptome seq from patient samples

  Exome sequencing data from FFPE preserved patient samples and patient-derived cultures. The goal of the study is to validate patient-derived cultures. Additional goal is to understand the relationship between omics and drug response.

  Study EGAS50000000172

• RNASeq profiles from Indian HFrEF Cohort

  The dataset contains whole transcriptomics profiling from a cohort of 49 HFrEF patients. The myocardium samples were collected from these patients during heart transplant of LVAD implantation procedure. The RNA samples were collected in RNAlater. Total transcriptome libraries were prepared using TruSeq Stranded Total RNA Library Prep with Ribo-Zero Gold kit and sequenced on Illumina HiSeq4000.

  Dataset EGAD50000001196

• GATA1 scD&D-seq integrated with Multiome

  Ex vivo differentiation experiments were performed using human CD34+ hematopoietic stem and progenitor cells along the erythropoietic trajectory at multiple timepoints (differentiation days 0, 5, 8, 18, and 24). Simultaneous profiling of transcriptome, chromatin accessibility, and GATA1 binding were performed by integrating D&D-seq with 10X Multiome.

  Dataset EGAD50000002299

• Transcriptome_Sequencing_of_Cancer_Cell_Lines

  In this study we will sequence the transcriptome of Verified Cancer Cell lines. This will be married up to whole exome and whole genome sequencing data to establish a full catalog of the variations and mutations found.

  Study EGAS00001000261

• GEOCODE Cohort

  We built a large cohort of 406 healthy individuals and expanded the immune cis-regulome through their whole blood transcriptome obtained after stimulation with specific toll-like receptor (TLR) agonists and T-cell receptor (TCR) antagonist

  Study EGAS50000000903

• Genome and transcriptome sequence data from a retroperitoneal leiomyosarcoma patient

  Genome and transcriptome sequence data from a retroperitoneal leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002583

• Genome and transcriptome sequence data from a endometrial carcinoma patient

  Genome and transcriptome sequence data from a endometrial carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001008921

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010951

• Genome and transcriptome sequence data from an uveal melanoma patient

  Genome and transcriptome sequence data from an uveal melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005824

• Genome and transcriptome sequence data from a pancreatic cancer patient

  Genome and transcriptome sequence data from a pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005841

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005849

• Genome and transcriptome sequence data from a pancreatic cancer patient

  Genome and transcriptome sequence data from a pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005855

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005858

• Genome and transcriptome sequence data from a pancreatic cancer patient

  Genome and transcriptome sequence data from a pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005867