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• Dynamics of genome architecture and chromatin function during human B cell differentiation and neoplastic transformation

  Despite recent advances, the dynamics of genome architecture and chromatin function during human cell differentiation and its potential reorganization upon neoplastic transformation remains poorly characterized. Here, we integrate in situ Hi-C and nine additional omic layers to define and biologically characterize the dynamic changes in three-dimensional (3D) genome architecture across normal B cell differentiation and in neoplastic cells from different subtypes of chronic lymphocytic leukemia (CLL) and mantle cell lymphoma (MCL) patients. Beyond conventional active (A) and inactive (B) compartments, an integrative analysis of Hi-C data uncovers a highly-dynamic intermediate compartment enriched in poised and polycomb-repressed chromatin. During B cell development, we detect that 28% of the compartments change at defined maturation stages and mostly involve the intermediate compartment. The transition from naive to germinal center B cells is associated with widespread chromatin activation, which mostly reverts into the naive state upon further maturation of germinal center cells into memory B cells. The analysis of CLL and MCL neoplastic cells points both to entity and subtype-specific alterations in chromosome organization. Remarkably, we observe that large chromatin blocks containing key disease-specific genes alter their 3D genome organization. These include the inactivation of a 2Mb region containing the EBF1 gene in CLL and the activation of a 6.1Mb region containing the SOX11 gene in clinically aggressive MCL. This study indicates that 3D genome interactions are extensively modulated during normal B cell differentiation and that the genome of B cell neoplasias acquires a tumor-specific 3D genome architecture.

  Study EGAS00001004763

• HPRU in Respiratory Infections DAC

  DAC to oversee data owned from the HPRU in Respiratory Infections at Imperial College London

  Dac EGAC50000000307

• Mutations in ALK signaling pathways conferring resistance to ALK inhibitor treatment lead to collateral vulnerabilities in neuroblastoma cells

  Study EGAS00001005791

• Molecular determinants of outcomes in relapsed mantle cell lymphoma treated with ibrutinib or temsirolimus in the MCL3001 (RAY) trial

  Study EGAS00001006342

• scRNA mCRC PDO

  scRNA of five mCRC organoids in basal conditions

  Study EGAS00001006214

• Engineering Immune Cells for Therapy, Institute for Medical Microbiology, Immunology and Hygiene, Technical University Munich

  CRISPR engineering of human T cells

  Dac EGAC50000000405

• Fastq files for SAIF genome

  This dataset contain the raw files generated for SAIF genome project

  Dataset EGAD00001000254

• Screening for human epigenetic variation at CpG islands

  Screening for human epigenetic variation at CpG islands

  Dataset EGAD00001000059

• SNP data for Ovarian cancer PRS

  SNP data for Ovarian cancer PRS (cases)

  Dataset EGAD00001008143

• 1506_Methylation_M.vd.Berge

  DNA methylation in bronchial biopsies of asthmatics, asthma in remission and healthy subjects

  Dataset EGAD00010001731

• Identifying causative mutations for Thrombocytopenia with Absent Radii

  Thrombocytopenia with Absent Radii is an inherited disorder that manifests itself with major limb skeletal abnormalities and low platelet count (and therefore a bleeding diathesis). The syndrome is well-characterised and defined phenotypically and there is a well-established database of UK-based families affected with ths disorder. The causative mutation for the disorder is yet to be identified. If known, it would allow for pre-natal screening and counselling avoiding life-long care for patients who are affected and are therefore severely disabled. We postulate that exon sequencing of 4 unrelated affected individuals would give enough power to narrow down potential candidate mutations which would thereafter be confirmed using DNA from other affected families.

  Study EGAS00001000054

• Genome-wide analysis for non alcoholic fatty liver disease

  Genome-wide association study for the 902 patients of non alcoholic fatty liver disease (NAFLD) including non alcoholic steato hepatitis (NASH) and hepatocellurar carcinoma and 7672 controls.

  Study JGAS000126

• WTCCC case-control study for Rheumatoid Arthritis

  WTCCC genome-wide case-control association study for Rheumatoid Arthritis (RA) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000011

• WTCCC case-control study for Type 1 Diabetes

  WTCCC genome-wide case-control association study for Type 1 Diabetes (T1D) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000014

• WTCCC case-control study for Type 2 Diabetes

  WTCCC genome-wide case-control association study for Type 2 Diabetes (T2D) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000016

• WTCCC case-control study for Coronary Artery Disease

  WTCCC genome-wide case-control association study for Bipolar disorder (CAD) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000003

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002922

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002921

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002919

• BLUEPRINT September 2016, ATAC-seq for germinal center B cell from tonsil, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for germinal center B cell from tonsil, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002917

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=6days from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=6days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002914

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002913

• BLUEPRINT September 2016, ATAC-seq for germinal center B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for germinal center B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002911

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002910

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002909

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002906

• BLUEPRINT September 2016, ATAC-seq for unswitched memory B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 3 sample(s) for unswitched memory B cell from venous blood, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002905

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002904

• BLUEPRINT September 2016, ATAC-seq for naive B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 3 sample(s) for naive B cell from venous blood, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002902

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for monocyte RPMI_LPS_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002901

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002900

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002899

• ChIP-seq fastq and alignment files

  ChIP-seq experiments: fastq files; both ChIP and Input for each sample. Illumina HiSeq 2500. ChIP-seq alignment files for trimmed, mapping q20 and nonredundant reads; both ChIP and Input for each sample. Software: Trim Galore v0.3.7; Bowtie 2 v2.1.0; samtools v1.7

  Dataset EGAD00001006279

• The Role of Myeloid Cells in Parkinson's Disease

  The Myeloid cells in Neurodegenerative Diseases (MyND) initiative is a collaborative effort with the goal of creating a multi-omic atlas of myeloid cells from the periphery and from autopsied brains of subjects with Parkinson’s disease (PD), Alzheimer’s disease (AD), and age-matched controls. We have generated large-scale transcriptomic profiles of CD14+ monocytes from 230 individuals with sporadic PD and age matched healthy subjects. We identified dysregulation of mitochondrial and proteasomal pathways, and single-cell analysis revealed that these pathways are enriched in the intermediate monocytes. We also generated transcriptomic profiles of primary microglia from autopsied brains of 55 PD and control subjects and observed discordant transcriptomic signatures of mitochondrial genes in PD monocytes and microglia/macrophages. ELISA NAVARRO*, EVAN UDINE*, et al. "Dysregulation of mitochondrial and proteolysosomal genes in Parkinson’s disease myeloid cells." Nature Aging, 2021. Link: https://www.biorxiv.org/content/10.1101/2020.07.20.212407v1PMID: 35005630

  Study phs002400

• Somatic Mosaicism in Amyotrophic Lateral Sclerosis and Frontotemporal Dementia

  The study was designed to investigate the role of somatic mosaic mutations in the pathogenesis of sporadic amyotrophic lateral sclerosis (sALS) and frontotemporal dementia (sFTD). A panel of molecular inversion probes (MIP) were used to target the exons and exon-intron junctions of 88 neurodegeneration-related genes. The panel included 34 ALS/FTD genes, 10 Alzheimer's disease genes, 28 Parkinson's disease genes, and 16 genes associated with other rare neurodegenerative disorders. The panel was used to perform ultra-deep sequencing on postmortem brain and spinal cord from 404 individuals with sALS or sFTD and 144 age-matched neurotypical controls. Known pathogenic germline mutations were found in 20.6% of ALS cases and 26.5% of FTD cases. Predicted pathogenic somatic mutations were observed in 2.7% of sALS and sFTD cases that did not have known germline mutations. The somatic variants had low variant allele fraction and region-specific enrichment, particularly in the primary motor cortex of sALS cases and prefrontal cortex of sFTD cases.

  Study phs003530

• Transcriptome alterations underlying metabolic dysfunction and liver disease in myotonic dystrophy type 1

  Myotonic dystrophy type 1 (DM1) is a multisystem disorder affecting various organs, including the skeletal muscles, eyes, heart, central nervous system, and endocrine system. Liver dysfunction and lipid metabolism abnormalities are frequently observed in DM1 but are not fully understood. To explore the molecular basis of these abnormalities, transcriptome analysis was performed on postmortem liver samples from DM1 patients DM1 patients (n = 11) and disease control patients (n = 9) using bulkRNA sequencing (RNA-seq) on the MGI DNBSEQ-G400RS. Differential gene expression and alternative splicing analyses revealed significant transcriptomic changes associated with lipid metabolism, liver fibrosis, and glucose homeostasis. Interestingly, transcriptome changes in DM1 livers also revealed partial resolution of sexual dimorphism in gene expression, along with unique sex-specific pathway alterations. A correlation between serum GGT levels and splicing abnormalities in DM1 patients was identified, suggesting a link between transcriptomic changes and clinical outcomes. This dataset provides valuable insights into the molecular mechanisms underlying DM1-related liver dysfunction and metabolic abnormalities.

  Study JGAS000814

• Homopolymer switches mediate adaptive mutability in mismatch repair-deficient colorectal cancer

  Mismatch repair (MMR) deficient cancer evolves through the continuous erosion of coding homopolymers in target genes. Curiously, the MMR genes MSH6 and MSH3 also contain coding homopolymers and these are frequent mutational targets in MMR-deficient cancers. The impact of incremental MMR mutations on MMR-deficient colorectal cancer evolution is unknown. We show that microsatellite instability modulates DNA repair by toggling hypermutable mononucleotide homopolymer runs in MSH6 and MSH3 through stochastic frameshift switching. Spontaneous mutation and reversion modulates subclonal mutation rate, mutation bias, and clonal HLA and neoantigen diversity. Patient-derived organoids corroborate these observations and show that in the absence of immune selection MMR homopolymer sequences drift back into reading frame, suggesting a fitness cost of elevated mutation rates. Combined experimental and simulation studies demonstrate that subclonal immune selection favours incremental MMR mutations. Overall, our data demonstrate that MMR-deficient colorectal cancers fuel intratumour heterogeneity by adapting subclonal mutation rate and diversity to immune selection.

  Study EGAS50000000297

• Heritable pulmonary arterial hypertension in a large Iberian family

  Data from a study of a large Iberian family (n=65 subjects, 5 generations) affected by pulmonary arterial hypertension (PAH) and segregating with the BMPR2 missense mutation p.Arg491Gln (rs137852749, c.1472G>A). PAH is a rare disease characterized by an abnormal rise in mean pulmonary arterial pressure (> or equal to 25 mmHg at rest), which, in turn, leads to a progressive increase in pulmonary vascular resistance and ultimately to death, due to right ventricular failure. Heritable PAH has an overall prevalence below 1 case per million adults and is defined by either the presence of a known genetic defect linked to the disease or a positive family history. Heritable PAH is inherited as an autosomal dominant disease. However, not all BMPR2 mutation carriers develop the disease, highlighting the presence of reduced penetrance. In this family, there are 22 mutation carriers from which 8 were diagnosed with heritable PAH and the other 14 were healthy at the time of examination.

  Study EGAS00001003123

• 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

• Super enhancers define regulatory subtypes and cell identity in neuroblastoma

  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 EGAS00001004551

• Genome-wide quantification of rare somatic mutations in normal human tissues using massively parallel sequencing

  We present Bottleneck Sequencing System (BotSeqS), a nextgeneration sequencing method that simultaneously quantifies rare somatic point mutations across the mitochondrial and nuclear genomes. BotSeqS combines molecular barcoding with a simple dilution step immediately prior to library amplification. We use BotSeqS to show age and tissue-dependent accumulations of rare mutations and demonstrate that somatic mutational burden in normal tissues can vary by several orders of magnitude, depending on biologic and environmental factors. We further show major differences between the mutational patterns of the mitochondrial and nuclear genomes in normal tissues. Lastly, the mutation spectra of normal tissues were different from each other, but similar to those of the cancers that arose in them. This technology can provide insights into the number and nature of genetic alterations in normal tissues and can be used to address a variety of fundamental questions about the genomes of diseased tissues.

  Study EGAS00001001838

• Dissecting features of epigenetic variants underlying cardiometabolic risk using full-resolution epigenome profiling in regulatory elements

  Sparse profiling of CpG methylation in blood by microarrays have identified epigenetic links to common diseases. We apply methylC-capture sequencing (MCC-Seq) in a clinical population of ~200 adipose tissue and matched blood samples (Ntotal ~400), providing high-resolution methylation profiling (>1.3M CpGs) at regulatory elements. We link methylation to cardiometabolic risk through associations to circulating plasma lipid levels and identify lipid-associated CpGs with unique localization patterns in regulatory elements. We show distinct features of tissue-specific versus tissue-independent lipid-linked regulatory regions by contrasting with parallel assessments in ~800 independent adipose tissue and blood samples from the general population. We follow-up on adipose-specific regulatory regions under (1) genetic and (2) epigenetic (environmental) regulation via integrational studies. Overall, the comprehensive sequencing of regulatory element methylomes reveals a rich landscape of functional variants linked genetically as well as epigenetically to plasma lipid traits.

  Study EGAS00001003415

• A longitudinal single-cell atlas of treatment response in pediatric AML

  Pediatric acute myeloid leukemia (pAML) is a disease characterized by heterogeneous cellular composition, driver alterations and prognosis. Characterization of this heterogeneity and how it affects treatment response remains relatively understudied in pediatric patients. We therefore used single-cell RNA sequencing and single-cell ATAC sequencing to profile 684,031 diagnosis, remission and relapse cells from 28 patients representing different pAML subtypes. Analysis revealed that at diagnosis, cellular compositions differed between distinct subgroups. Upon relapse, cellular hierarchies transitioned towards a more primitive state regardless of subtype. These primitive cells were distinct compared to cells at diagnosis, having underrepresentation of transcriptional programs involved in myeloid differentiation while programs commonly found in other lineages were overrepresented. In a subset of patients, this appeared to accompany the appearance of a B-lymphoid-like hierarchy. Together, our data reveal the emergence of apparent subtype-specific plasticity upon treatment and inform on potential novel therapeutic angles to target these cell populations.

  Study EGAS00001007323

• Somatic mutation and selection at epidemiological scale - TwinsUK_ExomeNanoSeq_Buccal

  Exome NanoSeq in buccal swab samples obtained from patients with a wide range of clinical phenotypes. 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 EGAD00001015620

• An IL-1β driven neutrophil-stromal cell axis fosters a BAFF-rich microenvironment in multiple myeloma

  The bone marrow is continuously occupied by high numbers of neutrophils, and a tumor-supportive bias of these cells could significantly impact bone marrow-confined malignancies. In multiple myeloma, the bone marrow is characterized by inflammatory stromal cells with the potential to influence neutrophils. Here, we investigated myeloma-associated alterations in marrow neutrophils and the impact of stromal inflammation on neutrophil function. Mature neutrophils in myeloma marrow are activated and tumor-supportive, transcribing increased levels of pro-inflammatory cytokines, including IL-1β, and myeloma cell survival factors, such as the BCMA-ligand BAFF. Neutrophils were re-activated after first-line treatment, while this regimen reduced, but did not normalize, stromal inflammation. Interactions with inflammatory stroma induced neutrophil activation, including BAFF secretion, in a STAT3-dependent manner and once activated, neutrophils gained the ability to reciprocally induce stromal activation. Combined, our data define the presence of a neutrophil-stromal cell feed-forward loop driving tumor-supportive inflammation that could impact disease recurrence.

  Study EGAS00001007038

• DAC for hepatoblastoma sequencing data

  Data Access Committee for sequencing data of hepatoblastoma PDX cell models sequenced under University of Helsinki.

  Dac EGAC50000000548

• RNA-seq data for NRF2 study

  RNA-seq data for clinical samples

  Dataset EGAD00001002243

• TTN gene targeted sequencing for AMC cohort

  TTN gene targeted sequencing for AMC cohort (n=24)

  Dataset EGAD00001005497

• Center for Education and Drug Abuse Research (CEDAR)

  Under its programmatic name, the Center for Education and Drug Abuse research (CEDAR), this Center of Excellence project was completed in 2015. The CEDAR sample consists of 775 nuclear families comprising an adult male (proband), his spouse/mate, and their biological child who is 10-12 years of age at recruitment. This child is designated as index child (IC), and is followed through age 30. Minimal exclusionary criteria were applied to maximize the sample's representativeness. Follow-up evaluations on ICs were conducted at ages 14, 16, 19, 22, 25, 27 and 30. Interim questionnaires were mailed annually beginning at age 20. CEDAR utilizes the family/high-risk paradigm. The offspring thus comprise high average risk (HAR) and low average risk (LAR) groups, constituting the majority of the CEDAR children sample: 250 HAR males, 100 HAR females, 250 LAR males and 94 LAR females. The remainder of the IC sample, 50 males and 31 females, are the offspring of fathers who have a lifetime non-SUD psychiatric dis-order. The follow-up rate from baseline to the final assessment is ~65%. The cohort of children is 76% White and 22% Black. The representation of females among ICs is lower than males, due to the later start of recruit-ment (2nd funding cycle; the study originally focused on males). The CEDAR genetic study has been augmented by the inclusion of its sample into the whole-genome genotyping effort conducted under the Genes, Environment and Development Initiative (GEDI). DNA from the blood samples of target children (index cases) and their siblings submitted to the NIDA Genetics Depository a Rutgers University was obtained and genotyped on Illumina Human660W-Quad Beadchips, with a high average genotyping rate of 99.8%. The sample comprised 158 females and 271 males (37 and 63 %), ~70:30 European- and African- American, with approximately 1:1 ratio of children of affected fathers and normal controls.

  Study phs001649

• Transcriptomic Analysis of HIV-Infected Cells

  Defining the attributes of rare CD4 T cells that harbor latent HIV under therapy with anti-retroviral agents has been challenging due to difficulties in identifying and isolating these cells. These cells represent an important barrier to cure, and characterizing them would aid the design and development of novel HIV cure strategies. In this study, we addressed this challenge using a custom microfluidic technology named Focused Interrogation of cells by Nucleic acid Detection and Sequencing (FIND-seq) that isolates HIV-infected cell transcriptomes, based on HIV DNA detection. We applied this method to HIV DNA+ memory CD4 T cells isolated from blood from five persons with HIV who were receiving anti-retroviral agents. After curating samples based on data quality, we proceeded with bioinformatics analysis from three persons. This analysis identified six transcriptomic pathways that were inhibited in HIV DNA+ cells compared to HIV DNA- cells. These included death receptor signaling, necroptosis signaling, and anti-proliferative G-alpha12/13 signaling. Furthermore, we identified two gene clusters, including 60 and 85 genes, that were significantly associated with HIV DNA+ cells identified by co-expression network analysis. These genes included negative regulators of HIV transcription that were higher in HIV DNA+ cells, positive regulators of HIV transcription that were lower in HIV DNA+ cells, and other genes involved in the negative regulation of mRNA translation, additional RNA processing functions, and the regulation of cellular state and fate. We further examined these signatures in transcriptomic data from CD4 T cell subsets sorted by flow cytometry from nine persons with HIV. We found a partial similarity between the smaller cluster of genes and the signature of CCR6- peripheral TFH cells. Raw sequencing data from all eleven human participant samples included in the study are available. These include samples from two participants who were studied only by FIND-seq, three participants who were studied by both FIND-seq and flow cytometry and six participants who were studied only by flow cytometry.

  Study phs003095