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• BLUEPRINT release August 2016, DNase-Hypersensitivity for macrophage - T=6days LPS, on genome GRCh38

  DNase-Hypersensitivity data for 4 macrophage - T=6days LPS sample(s). 6 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_dnaseseq_analysis_20160816

  Dataset EGAD00001002290

• BLUEPRINT release August 2016, DNase-Hypersensitivity for Acute Myeloid Leukemia, on genome GRCh38

  DNase-Hypersensitivity data for 37 Acute Myeloid Leukemia sample(s). 38 run(s), 37 experiment(s), 37 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_dnaseseq_analysis_20160816

  Dataset EGAD00001002355

• BLUEPRINT release August 2016, DNase-Hypersensitivity for macrophage - T=6days untreated, on genome GRCh38

  DNase-Hypersensitivity data for 4 macrophage - T=6days untreated sample(s). 6 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_dnaseseq_analysis_20160816

  Dataset EGAD00001002398

• SCLC CTC genomic analysis data set

  The data set consists of low-pass whole genome sequence data of single CTCs, pools of CTCs and germline controls for a cohort of 31 SCLC patients at both baseline, and for 5 patients at relapse. In addition 9 CDX models and associated germline controls (where available) are included.

  Dataset EGAD00001002678

• RNA-seq, ChIP-seq, ATAC-seq files for PCGP SJERG

  RNA-seq, ChIP-seq, and ATAC-seq files for PCGP SJERG paper titled "Deregulation of DUX4 and ERG in acute lymphoblastic leukemia"

  Dataset EGAD00001002681

• BLUEPRINT release August 2016, DNase-Hypersensitivity for Chronic Lymphocytic Leukemia, on genome GRCh38

  DNase-Hypersensitivity data for 2 Chronic Lymphocytic Leukemia sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_dnaseseq_analysis_20160816

  Dataset EGAD00001002459

• Clinical phenotypes/covariates

  This dataset contains the clinical phenotypes/covariates information for all the individuals. This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity.

  Dataset EGAD00001005040

• DigiPico sequencing data for the study of active mutational processes in HGSOC

  The dataset contains Bam files from DigiPico runs as well as bulk sequencing data used in the "A highly accurate platform for clone-specific mutation discovery enables the study of active mutational processes" publication.

  Dataset EGAD00001005118

• CRISPR screen M14, NCI-H3122 (2019-08-28)

  Genome wide CRISPR screen was performed to find resistance to targeted drugs for melanoma and lung . This dataset contains all the data available for this study on 2019-08-28.

  Dataset EGAD00001005296

• WGBS for T-Cell and B-Cell, control and tumor

  WGBS data for 75 paired fastq, spread over 31 samples (4 healthy T-cell, 7 healthy B-cell, 20 B-cell CLL tumors) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005970

• HV31 - Illumina PCR-free sequencing

  Illumina PCR-free sequencing data for individual HV31 generated using DNA from peripheral blood mononuclear cells, to a sequencing depth of ~44×. Sequencing was performed at the Wellcome Centre for Human Genetics on the Illumina Novaseq platform.

  Dataset EGAD00001007042

• CBD-KEY-CITESEQ-LINKER: Linker file for CITEseq sequencing data

  Linker file for COMBAT CITEseq sequencing data. Links COMBAT sample IDs with sequencing pools and their associated raw sequence data. Sequence data can be found in the following datasets: ADT data: EGAD00001007962 GEX data: EGAD00001008007 VDJ (B-cell): EGAD00001007964 VDJ (T-cell): EGAD00001007965

  Dataset EGAD00001008008

• A95629A

  Whole genome sequencing for single cells for library A95629A 1023 cells; filetype=bam

  Dataset EGAD00001006939

• A95673A

  Whole genome sequencing for single cells for library A95673A 1446 cells; filetype=bam

  Dataset EGAD00001006941

• A95703B

  Whole genome sequencing for single cells for library A95703B 1267 cells; filetype=bam

  Dataset EGAD00001006942

• A95728A

  Whole genome sequencing for single cells for library A95728A 876 cells; filetype=bam

  Dataset EGAD00001006943

• A96192B

  Whole genome sequencing for single cells for library A96192B 1304 cells; filetype=bam

  Dataset EGAD00001006944

• A96217B

  Whole genome sequencing for single cells for library A96217B 1616 cells; filetype=bam

  Dataset EGAD00001006945

• A96219B

  Whole genome sequencing for single cells for library A96219B 1743 cells; filetype=bam

  Dataset EGAD00001006946

• A98269B

  Whole genome sequencing for single cells for library A98269B 1609 cells; filetype=bam

  Dataset EGAD00001006947

• WES data generated in multifocal ileal NETs study

  This dataset includes whole-exome sequencing data for multifocal ileal tumor samples from two patients. Exonic sequences were enriched using the Agilent V2 capture probe set and sequenced by 76-bp paired-end reads using the Illumina Genome Analyzer IIx system with a mean coverage of 80x for each base

  Dataset EGAD00001006408

• CITE-seq for peripheral blood samples of 5 breast cancer patients

  We have 5 breast cancer patients who received VEN therapy. We collected their peripheral blood samples before and after long-term Venetoclax treatment. We apply CITE-seq protocol to these samples. This collection contains the all CITE-seq data for patients.

  Dataset EGAD00001008751

• Islet RFX6 Study Manuscript Data

  This submission includes raw FASTQ files (for bulk RNA-seq and 10X joint snATAC+snRNA multiome profiling experiments), sample phenotype files, and genotypes for the data included in the manuscript.

  Dataset EGAD00001008777

• Low Pass Whole Genome Sequencing of Cell Free DNA from Patients Receiving CD19 CAR T-Cell Therapy for Large B-Cell Lymphoma

  Low Pass Whole Genome Sequencing of Cell Free DNA from Patients Receiving CD19 CAR T-Cell Therapy for Large B-Cell Lymphoma consisting of 123 samples with FASTQs with hg19 aligned BAM/BAI files.

  Dataset EGAD00001009175

• RNAseq of liver harvested from CDAHFD mice treated for 8 weeks with either the MGAT2 inhibitor compound BMS-963272 or vehicle

  This experiment consists of RNAseq of liver harvested from CDAHFD mice treated for 8 weeks with either the MGAT2 inhibitor compound BMS-963272 (N = 10) or with vehicle (N = 10).

  Dataset EGAD00001009389

• Sequencing data for oesophageal / related samples - Kazachenka et al (RNA)

  Data supporting: "The transcriptional landscape of endogenous retroelements delineates esophageal adenocarcinoma subtypes" RNAseq for 279 samples

  Dataset EGAD00001011076

• Sequencing data for oesophageal and related samples - Ganguli et al (sWGS)

  Data supporting: "TBC" Ganguli et al (sWGS for 75 samples)

  Dataset EGAD00001011189

• Sequencing data for oesophageal and related samples - Abbas et al (RNA)

  Data supporting: "Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma" Abbas et al (RNA for 197 samples)

  Dataset EGAD00001011269

• RNA sequencing of control OM cells exposed to traffic-related air pollutants

  Total RNA sequencing of olfactory mucosa (OM) cells derived from cognitively healthy individuals exposed to traffic-related ultrafine particles (UFPs) for 24h and 72h in submerged cultures. The UFPs used for exposures were: A0, A20 and Euro6. Exposures were compared to the corresponding blank samples.

  Dataset EGAD00001011317

• Processed DNA methylome sequencing data

  The dataset contains methylation values of all SNP-filtered CpG sites for all samples from the air pollution study (total n=60). Nasal lavage samples were collected from n=29 moderately exposed (residing in Stuttgart) and n=31 lowly exposed (residing in Simmerath) individuals. For methods and study details, please see PMID 37343754.

  Dataset EGAD00001011208

• WGS files for paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

  WGS files for Klco paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

  Dataset EGAD00001015490

• WXS files for paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

  WXS files for Klco paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

  Dataset EGAD00001015491

• RNASeq files for paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

  RNASeq files for Klco paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

  Dataset EGAD00001015492

• MissionBio files for paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

  MissionBio files for Klco paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

  Dataset EGAD00001015493

• Single-Cell Data from "Spatiotemporal T-cell tracking for personalized T-cell receptor T-cell therapy designs in childhood cancer"

  This dataset contains the FASTQ files from the Single-Cell GEx+TCR 10X Genomics data from the study "Spatiotemporal T-cell tracking for personalized T-cell receptor T-cell therapy designs in childhood cancer" (EGAS00001008174)

  Dataset EGAD00001015632

• Mapping of runs back to samples for snRNASeq data

  Mapping of runs back to samples for PDN, PDO and TIS snRNASeq data. 4 sets of matched PDN, PDO and TIS samples (12 unique samples total) underwent pooled snRNASeq (Parse Biosciences). 2 sublibraries were created from this and sequenced at separate times

  Dataset EGAD00001015609

• TenK10K Phase 1: snATAC-seq FASTQ files

  Raw FASTQ files for single cell ATAC-sequencing data for PBMCs from the Tenk10k Phase 1 cohort (952 individuals pre-QC). Libraries were prepared using the 10x Genomics Chromium Next GEM Epi ATAC v2 kit and sequenced on the NovaSeq 6000 platform.

  Dataset EGAD50000002682

• ProHealth: Kaiser Permanente Genome-wide Association Study of Prostate Cancer

  A genome-wide association study (GWAS) of prostate cancer (PCa) was conducted in Kaiser Permanente (KP) Northern California health plan members (7,783 cases, 38,595 controls; 80.3% non-Hispanic white, 4.9% African-American, 7.0% East Asian, and 7.8% Latino) [PMID: 26034056]. The data for these members were drawn from three KP cohort studies: Research Program in Genes, Environment and Health (RPGEH) ProHealth, and California Men's Health Study (CMHS) (described further under Study History). Four custom arrays were designed for genotyping, one for each of the four major race-ethnicity groups in the RPGEH cohort: African Americans, East Asians, Latinos, and Non-Hispanic Whites. The number of SNPs and SNP content varied by array, with SNP content designed to maximize the genome-wide coverage of low frequency and more common variants specific to the different race-ethnicity groups, including newly identified SNPs from sequencing projects, and SNPs with established associations with disease phenotypes and risk factors [PMIDs: 21565264, 21903159]. Within the total study cohort, n=34,736 completed a consent which permitted deposition of data to NIH. Genotyping followed the same general procedure described in [PMIDs: 26092718, plus additional quality control (QC) steps for the additional men, in order to control for potential batch and kit effects, described in [PMID: 26034056. Briefly, we first repeated the filters described in [PMID: 26092718] for all four arrays (EUR, LAT, EAS, AFR). Then, on an array-wise basis, we removed SNPs with MAF<0.01, with a call rate<95%, or with Hardy-Weinberg Equilibrium (HWE) p-value in homogeneous groups<1x10ˆ-5. Furthermore, on the EUR array, to adjust for potential kit effect, we conducted a GWAS of kit, and removed those kit associated SNPs with p<1x10ˆ-6; we also re-genotyped each of the new samples (those not genotyped with the original GERA data) with some of the original GERA data, and removed SNPs with >13/1,268 (1%) mismatches. For the AFR array, to adjust potential plate batch issues, we conducted a GWAS of whether an individual was in the original GERA data vs. in the newly genotyped data and removed those batch-associated SNPs with p<0.05 (we used a stronger threshold than that used for the EUR array because there were fewer individuals on the AFR array); we also re-genotyped each of the new samples with the original GERA data and removed SNPs with >2/78 (2.6%). After the QC described above, imputation was performed as described in [PMID: 26034056]. Imputation was performed on an array-wise basis, pre-phasing with SHAPE-IT v2.5 [PMID: 22138821], and imputing from the 1000 Genomes Project October 2014 release as a cosmopolitan reference panel with IMPUTE2 [PMID: 22384356]. In addition to the GWAS described above, a nested exome-wide association study (EWAS) of PCa was also conducted (7,489 cases, 7,323 controls; 78% non-Hispanic white, 9% African-American, 3% East Asian, 6% Latino, 4% Other). A custom EWAS array primarily focused on rare variants was designed for genotyping that complemented the GWAS arrays [PMID: 26034056]. The EWAS array content included missense and loss-of-function mutations, and rare exonic mutations from The Cancer Genome Atlas (TCGA) and dbGaP prostate cancer tumor exomes [PMID: 26544944; PMID: 26544944]. Much of the EWAS array design content overlapped with the probesets on the UK Biobank Affymetrix Axiom array [PMID: 30305743]. Genotyping and QC steps taken to filter out samples exhibiting low quality and variants with low call rates are described in Emami et al., 2020 [biorXiv]. The resulting EWAS array genotypes are provided here.

  Study phs001221

• The Collaborative Study on the Genetics of Alcoholism (COGA)

  COGA is a family study of alcoholism, in which the subjects have been drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, ongoing family-based study that includes subjects from seven sites around the US. COGA has gathered detailed, standardized data on study participants, including diagnostic and neurophysiological assessments. This project has already proved successful in identifying several genes that influence the risk for alcoholism and neurophysiological endophenotypes, which have been independently replicated. COGA data were included as part of two Genetic Analysis Workshops, and the phenotypes are familiar to the genetics community. Alcoholic probands were recruited from treatment facilities, assessed by personal interview, and after securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through an alcoholic proband. Assessment involved a detailed personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Many participants also came to the laboratories for electroencephalographic studies. Neurophysiological features that have been shown to be useful endophenotypes for which we have linkage and in some cases association results, are included for a subset of the case-control sample: the beta power of the resting electroencephalogram (EEG), the P3(00) amplitude of the visual event-related potential (ERP), and the theta and delta event-related oscillations (EROs) underlying the P3. As part of COGA, a set of informative families was selected to have Genome-Wide Association data obtained within families. Genotyping was performed using the Illumina Human OmniExpress array 12.VI to genotype 2,282 subjects selected from 118 densely affected families. Genotyping was performed at the Genome Technology Access Center at Washington University School of Medicine in St. Louis. In addition, we also included genotypes for subjects (n=275 subjects) from these 118 families who were genotyped in a previous case-control GWAS using the Illumina 1M array. For quality control purposes, 51 of the 275 subjects were genotyped again on the Illumina Human OmniExpress array at the Washington University School of Medicine core facility.In addition, exome sequencing data on a subset of individuals with GWAS were added in version 2 (v2). For v2, a subset had 30X Whole Genome Sequencing (WGS) as part of the NIDA Sequencing Initiative. The subset contained two distinct sets: Sibling pairs where one sibling had at least two dependence diagnoses in the set (alcohol, cannabis, cocaine, and opioid), and the other had none, and non-related Case-Control pairs matched for age and ethnicity where the cases had alcohol and at least 2 other dependence diagnoses and controls had none. After sequencing, some sibling pairs are re-classified as half siblings. Three VCF files (small variants, structural variants, and copy number variations) are provided. Additional substance use variables are made available in v2. We note that the full sample data are deposited in four dbGaP submissions and the sequenced samples are split across all four: CIDR: Collaborative Study on the Genetics of Alcoholism Case Control Study [phs000125]. GWAS data on cases (primarily probands) and controls drawn from the families. Families with highest density of alcohol dependence and/or extreme event-related oscillation data [phs000763]. GWAS data on 119 extended families of European descent are available here, along with extensive documentation. Study on the Genetics of Alcoholism (COGA): African American Family GWAS [phs000976]. GWAS data on all available COGA families of African descent are available. COGA: Smokescreen GWAS [phs001208]. GWAS data on all remaining COGA DNA samples, primarily of other racial background, were genotyped on the Smoke Screen array. A listing of all sequenced pairs is provided in the documentation to facilitate the merging of these samples.

  Study phs000763

• Evaluation of Nuclear DNA from Rootless Hairs for Forensic Purposes

  The study aims to overcome current limitations in the recovery of DNA from small, difficult forensic samples. Particularly, our goal is to produce a robust laboratory protocol and the accompanying software to accelerate adoption, as well as to evaluate the reliability and robustness of both the laboratory and computational aspects of generating genotype files from minute and/or degraded DNA samples, such as single, rootless hairs.The data accompanying this study includes raw, paired-end reads from high-throughput sequencing of two panels of saliva, head hair, and pubic hair samples collected from anonymous volunteers at the University of California, Santa Cruz. The smaller set (Hair1.0) comprises 8 individuals, while the larger (Hair2.0) comprises 50 individuals, with 3 overlapping individuals between the two panels identified in post-collection analysis. We did not collect phenotype data or personally identifying information from the participants. For the Hair2.0 panel, only a subset of volunteers provided pubic hairs for DNA extraction and sequencing. Also included are saliva-derived genotype array data for all 8 individuals in the Hair1.0 panel and 44 of 50 individuals in the Hair2.0 panel.

  Study phs002979

• A Microwell Platform for High-Throughput Longitudinal Phenotyping and Selective Retrieval of Organoids

  In traditional bulk culture, organoids tend to overlap, hindering the analysis of individual organoid characteristics in a high-throughput manner. Additionally, variations in the local spatial properties of the bulk matrix make it challenging to distinguish whether phenotypic differences between organoids stem from inherent cellular disparities or disparities in the microenvironment. To address these challenges, we have developed a microwell-based technique that facilitates the quantification of image-based parameters for organoids grown from single cells. Furthermore, these organoids can be easily retrieved from their respective microwells for molecular profiling. By employing a deep-learning image processing pipeline, we conducted a comprehensive assessment of various phenotypic traits in two CRISPR-engineered human gastric organoid models. This analysis encompassed growth rates, cellular movement, and apical-basal polarity. Through our investigation, we successfully identified genomic alterations associated with increased growth rate, as well as changes in accessibility and expression patterns correlated with apical-basal polarity. This novel methodology offers a valuable tool for studying organoid behavior at a single-cell level, enabling researchers to gain deeper insights into organoid biology and associated genetic modifications.

  Study phs003315

• Genetic Underpinnings of Ethnic Disparities in Bone Toxicities Between Hispanic and Non-Hispanic Children Treated for Acute Lymphoblastic Leukemia

  Acute lymphoblastic leukemia (ALL) is the most common malignancy among children and young adolescents. More than 90% of children are cured with a combination of multiple chemotherapeutic drugs. Some may suffer from debilitating toxicities due to the cytotoxic drugs, necessitating pharmacogenetic research to search for genetic markers predictive of treatment toxicities, so that treatment can be better tailored based on patients' genetic makeup. Bone toxicities, including osteonecrosis and fractures, most often due to glucocorticoids, are the most common complications in ALL, which have long-lasting detrimental impact on the still developing skeletons in children. In DFCI ALL Consortium Protocol 05-001, a multi-center clinical trial for childhood ALL conducted in Canada and the US, we found that Hispanic children had less drug toxicities to their bones than non-Hispanic children. Although reasons for the observed ethnic differences are largely unknown, patients' inherited genetic background may be at play. This study seeks to perform a novel pharmacogenomic study based on multi-site clinical trials DFCI ALL Consortium Protocol 05-001 and 11-001 to identify genetic underpinnings of ethnic disparities in bone toxicities.

  Study phs002317

• CONNECTS Master Protocol for Clinical Trials targeting Macro- and Micro-Immuno-Thrombosis, Vascular Hyperinflammation, and Hypercoagulability and Renin-Angiotensin-Aldosterone System (RAAS) in Hospitalized Patients with COVID-19 (ACTIV-4 Host Tissue)

  ACTIV 4 Host Tissue is a shared-placebo clinical trial platform evaluating therapies targeting the host response to COVID-19 in hospitalized patients. The overarching goal of the platform was to find effective strategies for inpatient management of patients with COVID-19. Therapeutic goals for patients hospitalized for COVID-19 include hastening recovery and preventing progression to critical illness, multiorgan failure, or death. Our objective is to determine whether modulating the host tissue response improves clinical outcomes among patients with COVID-19. Three trials were implemented to investigate three agents: TXA-127, TRV-027, and Fostamatinib. These agents all impact the host tissue response in COVID-19 via a number of unique mechanisms, including potential beneficial effects on the RAAS system and formation of neutrophil extracellular traps (NETs). Each trial evaluated the efficacy of these agents' ability to impact the host tissue response and improve outcomes in patients hospitalized with COVID-19. We found no evidence that any of the three agents significantly improved clinical outcomes as measured by the primary outcome, oxygen free days through day 28.

  Study phs003708

• Final results and ctDNA analyses from the randomized phase 3 IMpassion031 trial evaluating peri-operative atezolizumab for early-stage triple-negative breast cancer

  In IMpassion031, adding atezolizumab to neoadjuvant chemotherapy significantly improved pathologic complete response (pCR) rate (primary endpoint) for stage II/III triple-negative breast cancer (TNBC). Patients with stage II/III TNBC were randomized 1:1 to neoadjuvant chemotherapy plus peri-operative atezolizumab or pre-operative placebo. Descriptive secondary endpoints included event-free, disease-free, and overall survival. Long-term outcomes favored the atezolizumab group (event-free survival HR 0.76, 95% CI: 0.47–1.21). Among patients without pCR, 14/70 (20%) atezolizumab-treated and 33/99 (33%) placebo-treated patients received additional adjuvant therapy, frequently capecitabine. In exploratory analyses, pCR was prognostic for long-term outcome. Patients with baseline ctDNA-negative status (6%) had excellent long-term outcomes. Most patients (87%) had cleared ctDNA at surgery. ctDNA-positive status at surgery identified a subset of non-pCR patients with poorest prognosis. Long-term safety was consistent with primary results. Adding atezolizumab to chemotherapy for stage II/III TNBC is associated with more favorable long-term outcomes. ctDNA dynamics provide prognostic value beyond pCR. ClinicalTrials.gov identifier: NCT03197935

  Study EGAS50000000974

• The identification of genetic vulnerabilities in head and neck cancers for the development of novel treatments.

  The global cancer burden is expected to double by the year 2030 and this will disproportionately affect the Asian continent. Head and neck squamous cell carcinoma (HNSCC) is endemic in Asia. It is the sixth most common cancer worldwide and the second most common in Malaysia, with approximately 600,000 new cases per year globally. Longterm survival remains less than 50%, underscoring the need for better therapeutic strategies. In this proposal we aim to bring new technological advancements in the identification of critical genes in HNSCC and the identification of compounds for the development of new therapies in HNSCC. We propose to genomically characterise 16 unique Asian H&N cancer cell lines, to classify sub groups where identification of essential genes that can be targeted for tumor control can be applied in a more rational way. Further, we propose to use zebrafish, an established drug discovery platform to identify promising pathway-specific compounds that could be further studied using CRISPR/Cas9 lethality screens and biological models to better identify novel therapeutic strategies to combat this major health problem in Asia.

  Study EGAS00001002682

• DynaTag for efficient profiling of transcription factors in small samples and single cells

  Systematic discovery of transcription factor (TF) landscapes in low-input samples and at single cell level is a major challenge in the fields of molecular biology, genetics, and epigenetics. To address this, we present here cleavage under Dynamic targets and Tagmentation (DynaTag), which allows robust mapping of specific TF-DNA interactions via the use of a physiological salt solution during sample preparation. Using this method, we revealed occupancy alterations for 15 different TFs in stem cell and cancer tissue models. Of note, we showcased for NANOG, MYC, and OCT4 differentially occupied genomic loci during stem cell differentiation, both in bulk and at single-cell resolution. DynaTag demonstrated superior signal-to-background ratio and occupancy resolution in comparison to CUT&RUN and ChIP-seq. In addition, a model for small cell lung cancer chemotherapy treatment in vivo showed increased chromatin occupancies of the gain-of-function mutant P53 p.R248Q, FOXA1, and MYC at altered gene pathways, such as epithelial-mesenchymal-transition. Altogether, these results highlight the technical advancement of DynaTag to uncover TF landscapes in cell models and in tissues of a complex disease model.

  Study EGAS50000001074

• Dental Caries: Whole Genome Association and Gene x Environment Studies

  Dental caries (also known as tooth decay) remains the most common chronic disease of childhood, five times more common than asthma and seven times more common than environmental allergies, with more than 40% of children exhibiting caries when they enter kindergarten. In 2005, it was estimated that dental health care costs were approximately $84 billion, of which 60% or about $50 billion were related to treatment of dental caries. Although overall caries prevalence has declined over the last 40 years, dental caries in the primary dentition and mean caries rates in children ages 2-11 has increased markedly over the past 12 years. Childhood caries is a serious public health issue because of associated health problems and because disparities in oral health have led to substantially higher average disease prevalence among children in poverty and in under-served racial and ethnic groups. These issues are of such concern that in 2005, the American Academy of Pediatrics made children's oral health one of their top areas of focus, as it is for the majority of the NIDCR "Disparities Centers". The etiology of dental caries has been studied for many years. Multiple factors contribute to a person's risk for caries, including: 1) environmental factors such as diet, oral hygiene, fluoride exposure and the level of colonization of cariogenic bacteria and 2) host factors such as salivary flow, salivary buffering capacity, position of teeth relative to each other, surface characteristics of tooth enamel and depth of occlusal fissures on posterior teeth. In spite of all that is known about this disease, there are still individuals who appear to be more susceptible to caries and those who are extremely resistant, regardless of the environmental risk factors to which they are exposed, implying that genetic factors also play an important role in caries etiology. This conclusion is supported by studies in both humans and animals, with the most compelling evidence coming from studies of twins reared apart in which investigators found significant resemblance within monozygotic (MZ) but not dizygotic (DZ) twin pairs for percentage of teeth and surfaces restored or carious and estimated the genetic contribution to caries as 40%. Other recent studies of twins reared together estimated the heritability for caries, adjusted for age and gender, as ranging from 45-64%. Despite the strong evidence of a genetic component to risk for dental caries, there have been only a few studies of candidate genes in caries, and no published genome-wide scans. A comprehensive genome wide search is the only approach that will allow us to identify those genetic regions likely to harbor genes increasing the risk for dental caries, and eventually to identify the etiologic genes and to explore the interaction of those genes with microbiological, dietary, fluoride, and behavioral factors that are known to be associated with caries risk and progression. Therefore, the goal of this study is to perform genome-wide association (GWA) studies of dental caries with a large panel of SNP's (610,000) in families and individuals ascertained through multiple US sites (University of Pittsburgh and University of Iowa). The v2 release of this study includes 96 additional individuals who were genotyped with the CCDG: Dental Caries and CL/P in Guatemala project (dbGaP accession number phs000440) to augment the data initially presented here. These subjects were genotyped on the Illumina 610 platform to make their data comparable. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org), which was developed through the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to dental caries through large-scale genome-wide association studies of well-characterized families and individuals at multiple sites in the U.S. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). The study was supported by the National Institute of Dental and Craniofacial Research (NIDCR, U01-DE018903). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington. Samples of some participants in this study were selected for further genomic analysis. These results will be available in the dbGaP CIDR study: Center for Oral Health Research in Appalachia (COHRA) Genomic Studies of Oral Health and Disease (phs001591).

  Study phs000095

• Risk Assessment of Cerebrovascular Events (RACE) Study

  This study includes 1,220 cases with young onset stroke (stroke before age 60 years) who are participants of the larger RACE study. Risk Assessment of Cerebrovascular Events (RACE) is an on-going existing case-control study of stroke now involving over 5000 imaging confirmed cases of stroke and 5000 controls, recruited from seven centers in Pakistan. The study is aimed to investigate the genetic, biomarker and lifestyle determinants of stroke and its subtypes. Cases are eligible for inclusion in the study if they: (i) are aged at least 18 years; (ii) present with a sudden onset of neurological deficit respecting a vascular territory with sustained deficit at 24 hours verified by medical attention within 72 hours after onset (onset is defined by when the patient was last seen normal and not when found with deficit); and (iii) the diagnosis is supported by CT/MRI; and (iv) present with a Modified Rankin Score < 2 prior to the stroke. Findings from patient's history, 12-lead ECG and CT or MRI of the brain. The mandatory procedures for inclusion in this investigation are: (i) clinical verification of cerebrovascular event within 72 hours of onset; (ii) neuroimaging CT (non-contrast) or MRI (MRI is not a mandatory investigation but recorded whenever ordered by the attending physician); and (iii) 12-lead ECG. All other ancillary investigations ordered by the attending physician are recorded as well. The TOAST classification method is used to classify ischemic stroke based on aetiology whereas the Oxfordshire classification is used to classify stroke neuro-anatomically. Control participants for this subset of young onset stroke were individuals enrolled in the Pakistan Risk of Myocardial Infarction Study (PROMIS), a case-control study of acute MI based in Pakistan. RACE capitalizes on the genetic data (including information on GWAS) that has already been collected from the healthy participants enrolled in PROMIS. RACE and PROMIS share similar methodology of recruitment. Participants from both these investigations are derived from similar catchment areas, hence providing an attractive opportunity for RACE to utilize PROMIS controls as common controls for genetic investigations. Controls in PROMIS were recruited following procedures and inclusion criteria as adopted for RACE cases. In order to minimize any potential selection biases, PROMIS controls selected for this stroke substudy were frequency matched to RACE cases based on age and gender and were recruited in the following order of priority: (1) non-blood related or blood related visitors of patients of the out-patient department; (2) non-blood related visitors of stroke patients; (3) patients of the out-patient department presenting with minor complaints (e.g. back pain, minor gastric complaints). Control subjects from the PROMIS study were genotyped at the Wellcome Trust Sanger Institute on the Illumina 660W Quad array. The Center for Non-Communicable Diseases, Pakistan, serves as the coordinating center for both RACE and PROMIS. More information on these research investigations can be found at www.cncdpk.com. This young onset stroke component to the RACE study was funded through the Gene Environment Association Studies initiative (GENEVA, www.genevastudy.org as one of three studies designed to assess the genetics of young onset stroke and modification of genetic effects by smoking. GENEVA is part of the trans-NIH Genes, Environment, and Health Initiative (GEI). Genotyping of 1,220 young onset stroke cases was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to stroke through large-scale genome-wide association studies of cases and controls recruited within Pakistan. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000456

• Detection of rare mutations, copy number variation, and DNA methylation in the same template DNA molecules

  The analysis of cell-free DNA (cfDNA) from plasma offers great promise for the earlier detection of cancer. At present, changes in DNA sequence, methylation, or copy number are the most sensitive ways to detect the presence of cancer. To further increase the sensitivity of such assays with limited amounts of sample, it would be useful to be able to evaluate the same template molecules for all these changes. Here we report an approach, called MethylSaferSeqS, that achieves this goal, and can be applied to any standard library preparation method suitable for massively parallel sequencing. The innovative step was to copy both strands of each DNA-barcoded molecule with a primer that allows the subsequent separation of the original strands (retaining their 5-methylcytosine residues) from the copied strands (in which the 5-methylcytosine residues are replaced with unmodified cytosine residues). The epigenetic and genetic alterations present in the DNA molecules can then be obtained from the original and copied strands, respectively. We applied this approach to plasma from 265 individuals, including 198 with cancers of the pancreas, ovary, lung and colon, and found the expected patterns of mutations, copy number alterations, and methylation. Furthermore, we could determine which original template DNA molecules were methylated and/or mutated. MethylSaferSeqS should be useful for addressing a variety of questions relating genetics and epigenetics in the future.

  Study EGAS00001006839

• Genetics of Chemotherapy Induced Peripheral Neuropathy in N08C1 and N08CB

  Chemotherapy-induced peripheral neuropathy (CIPN) is a common and potentially dose-limiting toxicity of chemotherapy treatment. CIPN severity varies widely between cancer patients, and previous studies had found evidence of genes and single nucleotide variants (SNV) being associated with CIPN. The goal of this study was to further identify genetic markers and pathways associated with CIPN severity using whole exome sequencing (WES) and whole genome sequencing (WGS) of participants in two clinical studies which collected longitudinal patient-reported outcome (PRO) measures of CIPN. NCCTG/Alliance study N08C1 was a prospective cohort study of the natural history of paclitaxel-associated acute pain syndrome (P-APS) and CIPN. NCCTG/Alliance trial N08CB was a randomized, placebo-controlled trial of calcium and magnesium for prevention of oxaliplatin-induced sensory neuropathy in which the treatment had no significant effect on either acute pain or sensory neuropathy. Both N08C1 and N08CB collected patient assessments of CIPN symptoms before each cycle of chemotherapy using the EORTC QLQ-CIPN20 instrument. For this study, CIPN cases were selected from each of N08C1 and N08CB as those patients with the most severe CIPN symptoms (assessed longitudinally). CIPN controls were selected as those with the least severe symptoms. WGS was obtained for N08C1 samples (WES had been obtained and analyzed previously), and WES was obtained for N08CB samples.

  Study phs001480