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• National Institute of Neurological Disorders and Stroke (NINDS), Family Study of Essential Tremor (FASET), Identification of Susceptibility Genes for Essential Tremor

  The Familial Study of Essential Tremor (FASET) was designed to identify susceptibility genes for Essential Tremor. ET is among the most common neurological diseases with a prevalence (age > 40 years) estimated to be 4.0% and prevalence in advanced age (> 90 years) exceeding 20%. ET, often referred to as "familial tremor", is generally regarded as a highly genetic disorder with families, with affected members over multiple generations, and twin studies show high concordance among monozygotic twins. Probands (affected with ET) and relatives were enrolled in a family study of ET at Columbia University, New York between 2011 - 2014. The study was approved by the Institutional Review Board at Columbia University and written informed consent was obtained from all enrollees. The criteria for enrollment were: 1) the proband had early-onset ET with age at onset < 50 years, 2) the proband had a diagnosis of definite or probable ET, 3) in addition to the proband, there were at least two affected relatives in the family, 4) additional affected and unaffected family members were willing to participate in the study, and 5) the families contained more than two affected individuals in different generations. Blood samples were also collected for genetic research. For the genetic analyses, we excluded enrollees that we or others had diagnosed with Parkinson's disease (PD) or dystonia. The final sample includes 52 families (52 probands [affected with ET]) and 155 relatives). The number of affected individuals enrolled per family ranged from 3 - 7 (mean = 4.1). Genetic samples from FASET were analyzed with whole genome SNP genotyping (for linkage analyses) and whole exome sequencing. It is hoped that this resource will better help researchers to understand the genetic causes of ET and underlying disease pathogenesis.

  Study phs000966

• Base modification analysis using single molecule real-time sequencing

  This dataset was generated using single-molecule real-time sequencing for both training and testing purposes. The DNA samples isolated from human buffy coats or placenta of healthy individuals (n=4,) were prepared in a way that four types of base modifications were incorporated, including unmodified controls, 5mC, 5hmC, and 6mA. The sequence data for each sample consists of subreads produced by single-molecule real-time sequencing and stored in a bam format. Details of the specific experiments conducted in this study are outlined in our manuscript.

  Dataset EGAD50000000541

• 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.

  Study EGAS50000000182

• RNA-sequencing of adult T-cell leukemia/lymphoma samples

  Adult T-cell leukemia/lymphoma (ATL) is a highly aggressive hematological malignancy derived from mature CD4+ T-lymphocytes. In this study, we performed RNA-sequencing (RNA-seq) analysis for ATL samples including 9 primary tumors and 1 ATL cell line to clarify gene expression profiles in this disease.

  Study EGAS00001003575

• The effect of anti-HER2/CD3 TDB on transcription in human CD8 T cells (bulk RNA-seq)

  RNA was isolated from purified human CD8 cells that were incubated with anti-HER2/CD3 TDB in the presence of SK-BR-3 cells. Sequencing libraries were generated and submitted for transcriptome profiling by high-throughput sequencing. Experiments were performed in triplicates for anti-HER2/CD3 TDB treatment and control. This Dataset is associated with the following ArrayExpress Experiment: E-MTAB-8211 - The effect of anti-HER2/CD3 TDB on transcription in human CD8 T cells (bulk)

  Dataset EGAD00001005187

• Mortality and risk of progression to adult T-cell leukemia/lymphoma in patients with HTLV-1-associated myelopathy/tropical spastic paraparesis

  Human T-cell leukemia virus (HTLV)-1 causes the functionally debilitating disease HTLV-1-associated myelopathy/ tropical spastic paraparesis (HAM/TSP) as well as adult T-cell leukemia lymphoma (ATLL). Although there were concerns that the mortality of HAM/TSP could be affected by the development of ATLL, prospective evidence was lacking in this area. In this 5-year prospective cohort study, we determined the mortality, prevalence, and incidence of ATLL in 527 HAM/TSP patients. The standard mortality ratio of HAM/TSP patients was 2.25, and ATLL was one of the major causes of death (5/33 deaths). ATLL prevalence and incidence in these patients were 3.0% and 3.81 per 1,000 person-years, respectively. To identify patients at a high risk of developing ATLL, flow cytometry, Southern blotting, and targeted sequencing data were analyzed in a separate cohort of 218 HAM/TSP patients. In 17% of the HAM/TSP patients, we identified an increase in T-cells positive for cell adhesion molecule 1 (CADM1), a marker for ATLL and HTLV-1 infected cells. Genomic analysis of these patients revealed that somatic mutations of HTLV-1 infected cells were seen in 90% of the cases and 11% of them had dominant clone and developed ATLL in the longitudinal observation. In this study, we were able to demonstrate for the first time that the increased mortality in patients with HAM/TSP and a significant effect of ATLL on their prognosis. Having dominant clonal expansion of HTLV-1- infected cells with ATLL-associated somatic mutations may be important characteristics of patients with HAM/TSP who are at an increased risk of developing ATLL.

  Study JGAS000226

• Phylogenetic analysis of treatment-naive metastases using whole exome and genome sequencing data

  Metastases are responsible for the majority of cancer related deaths and are often difficult to treat successfully. Even for metastases that occur subsequent to treatment, we do not know whether such relapsing metastases were originally heterogeneous or if the observed heterogeneity is a consequence of therapy. Given that treatment can influence evolutionary dynamics by selecting resistant clones, imposing bottlenecks on cancer cell populations, and even inducing novel somatic mutations, characterizing the prior standing variation among metastases remains an important goal to predict initial therapeutic response. To quantify the heterogeneity at clinical presentation of advanced disease, we surveyed the literature for patients in which at least two treatment-naïve metastases underwent genome/exome-wide sequencing. Across all cancer types surveyed, only 18 subjects were found to fulfill this requirement. Including previously unpublished data from two subjects, we analyzed data of 74 untreated metastases and inferred cancer phylogenies. Putative driver gene mutations were acquired at a 2-fold higher rate on the trunk of all metastases than on branches. Mutations in driver genes along the trunk were strongly enriched for predicted functional consequences. Using a stochastic mathematical model, we find that driver gene heterogeneity among metastases mostly occurs in slowly growing cancers for highly advantageous driver gene mutations. Seeding efficiency only weakly affects the heterogeneity among metastases. These results explain why functional driver gene heterogeneity is uncommon in advanced disease prior to treatment, thus providing optimism for future therapies that depend on mutations across metastases.

  Study EGAS00001002777

• Whole-Exome Sequencing Plasma Control Samples for Benchmarking

  This study contains whole-exome sequencing plasma and HapMap (12877, 12878) control samples for bioinfomatic bencmarking. Plasma samples contain variations in the genes KRAS, NRAS, PIK3CA, and EGFR, including insertions and deletions, at 0.0%, 0.1%, 1.0%, and 5.0%.

  Study EGAS50000000565

• Lam-ESC&Lam-Recombination data

  This dataset includes all data produced in the study describing "Lam-ESC&Lam-Recombination", a method for sequencing of signal joints and coding joints generated from human light chain antigen receptor loci during V(D)J recombination in B-cell precursor acute lymphoblastic leukaemia (BCP-ALL) patients. This dataset includes: - Amplicon Lam-ESC for a total of 86 BCP-ALL patients - fastq files - Amplicon Lam-Recombination for a total of 43 BCP-ALL patients - fastq files

  Dataset EGAD50000000597

• Gene-Environment Interactions (GxE) and Complex Traits

  Functional variants associated with complex traits tend to fall in non-coding regions and affect regulatory mechanisms that are not yet well characterized. Furthermore, it is generally difficult to determine in which tissues and conditions they may have a functional impact. This is because the effect of a genetic variant on a molecular pathway, and ultimately on the individual's phenotype, may be modulated by "environmental" factors. We denominate such variants "gene-expression environment-specific quantitative trait nucleotides" GxE-QTNs. Achieving a better understanding of the mechanisms underlying GxE is a critical step in understanding the link between genotype and complex phenotype. It is also crucial to develop computationally efficient and statistically sound methods capable to integrate tissue/condition-specific functional genomics data to predict and validate when a sequence variant is functional. In this study we developed novel experimental and computational approaches to screen, analyze and functionally characterize genetic variants for complex traits modulated by environmental exposures. To identify and characterize genes with GxE, we analyzed allele specific gene expression in a panel of five relevant tissues (e.g. the vascular endothelium for cardiovascular diseases) under 50 controlled environmental conditions (e.g. glucocorticoids treatment, as a proxy for stress exposure). These data should be useful to develop computational tools that integrate different sources of evidence including data collected by ENCODE, RoadMap Epigenome and GTEx projects to functionally annotate GWAS variants. The experimental and computational tools developed by this project have widespread applicability, for example, can be used to tackle the functional basis of complex traits in other environmental contexts (e.g. other types of stress and hormonal levels) and genetic backgrounds. This resource represents the first comprehensive catalog of genetic variants that interact with environmental exposure in determining human complex traits.

  Study phs001176