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• Exome sequencing of DNA from pituitary neuroendocrine tumor (PitNET) and germline DNA from the same patient

  The goal of the project is to study tumor - normal DNA pairs from the PitNET patients. Total of 15 PitNET patients were recruited for the study to investigate sometic changes in the tumor compared to normal tissue. Illumina technology were used for sequencing and two data analysis pipelines employed for data analysis. Recurrent somatic variations were investigated and genomic disruption analysis from exome sequencing data attempted.

  Study EGAS00001004654

• (Epi)genetic Risk Architectures of Opioid-Dependent Brain

  With nearly 20,000 overdose deaths in 2014 alone, opioid addiction (OA) has emerged as one of the most pressing public health crises in recent US history. One-fifth of individuals who try heroin develop an addiction to opioids. Genetics is a major contributor to OA with an estimated 60% heritability, only somewhat less than schizophrenia (80%) which has recently seen substantial gains in identified underlying genetics. Yet, studies to date have failed to uncover most of the genes that predispose individuals to OA, leaving the overwhelming fraction of OA heritability unexplained. The proposed study takes a novel, integrated "omics-based" strategy to investigate the molecular basis of OA and uncover both genetic and epigenetic factors associated with opioid addiction. The premise for our approach is founded on studies from our labs, and others, implicating regulatory variation in common traits and diseases, including those associated with complex brain phenotypes like addiction. We have collected the largest known cohort of postmortem brains from addicts who overdosed on opioids, along with matched control brains from non-users. From both cases and control specimens, we will isolate cells from 2 regions of the brain closely implicated in the addiction phenotype: the Prefrontal Cortex (PFC) and the Nucleus Accumbens (NAc). In Aim 1, we propose ChIP-seq studies to identify regulatory elements that distinguish cases from controls and define the opioid addiction phenotype. The regulatory differences will be connected to their gene targets through high resolution in situ Hi-C. In Aim 2, we propose QTL-based approaches to identify genetic variants that underlie the regulatory differences (hmQTLs). We also propose eQTL analyses to identify genetic variants that underlie differences in transcript levels between cases and controls. Aim 3 leverages the largest heroin addiction GWAS meta-analysis to date to test the hypothesis that SNPs in regions associated with chromatin and expression differences between cases and controls define novel loci for predisposition to OA. Each Aim has the potential for discovery independent of the others (differential HM, RNAexp, QTLs, and variant-phenotype associations) but their synergy is the most powerful component of the proposed study: identifying regulatory pathways that generate, not only phenotype associations, but hypothesized mechanisms for those associations which can be the focus of new opioid addiction prevention and treatment development.

  Study phs002724

• Region-specific Transcriptome Analysis of the Human Retina and Retinal Pigment Epithelium (RPE)/Choroid

  Proper spatial differentiation of retinal cell types is necessary for normal human vision. Many retinal diseases, such as Best disease and male germ cell associated kinase (MAK)-associated retinitis pigmentosa, preferentially affect distinct topographic regions of the retina. While much is known about the distribution of cell types in the retina, the distribution of molecular components across the posterior pole of the eye has not been well-studied. To investigate regional difference in molecular composition of ocular tissues, we assessed differential gene expression across the temporal, macular, and nasal retina and retinal pigment epithelium (RPE)/choroid of human eyes using RNA-Seq. RNA from temporal, macular, and nasal retina and RPE/choroid from four human donor eyes was extracted, poly-A selected, fragmented, and sequenced as 100 bp read pairs. Digital read files were mapped to the human genome and analyzed for differential expression using the Tuxedo software suite. Retina and RPE/choroid samples were clearly distinguishable at the transcriptome level. Numerous transcription factors were differentially expressed between regions of the retina and RPE/choroid. Photoreceptor-specific genes were enriched in the peripheral samples, while ganglion cell and amacrine cell genes were enriched in the macula. Within the RPE/choroid, RPE-specific genes were upregulated at the periphery while endothelium associated genes were upregulated in the macula. Consistent with previous studies, BEST1 expression was lower in macular than extramacular regions. The MAK gene was expressed at lower levels in macula than in extramacular regions, but did not exhibit a significant difference between nasal and temporal retina. The regional molecular distinction is greatest between macula and periphery and decreases between different peripheral regions within a tissue. Datasets such as these can be used to prioritize candidate genes for possible involvement in retinal diseases with regional phenotypes. Reprinted from Whitmore, S.S., Wagner, A.H., DeLuca, A.P., Drack, A.V., Stone, E.M., Tucker, B.A., Zeng, S., Braun, T.A., Mullins, R.F., Scheetz, T.E., 2014. Transcriptomic analysis across nasal, temporal, and macular regions of human neural retina and RPE/choroid by RNA-Seq. Experimental Eye Research. Used under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported license. Additional RNA sequencing was performed on temporal, macular, nasal, inferior, and superior retina from a fifth subject and is included in this dataset. See original publication for details.

  Study phs001151

• Genome_Diversity_in_Africa_Project__Benin

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene–disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region.The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group).Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformaticsThis data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001688

• Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation

  As part of the study "Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation" we wanted to identiffy the SNVs that are located in STRC and which ones in STRCP1. For this we applied targeted long-read sequencing.

  Dataset EGAD00001011305

• High-throughput determination of the antigen specificities of T cell receptors in single cells

  High-throughput linking of T cell receptor (TCR) sequences to their binding antigens is vital for immune profiling, yet challenging. We present Tetramer associated TCR Sequencing (TetTCR-Seq) to address this challenge. Binding is determined using a library of DNA-barcoded antigen tetramers that are rapidly and inexpensively generated using an in vitro transcription/translation platform. We included CMV+ donors (CMV seropositive donors who are infected with Cytomegalovirus) to screen for CMV specific TCRs.

  Study phs001678

• Genomic Data Access Committee for Early and Late Onset Colorectal Cancer Study

  This Data Access Committee (DAC) manages access to genomic data generated from the study "A Clinically and Genomically Annotated Early Onset Colorectal Cancer and Late Onset Colorectal Cancer." The study focuses on identifying the distinct genomic profiles of early-onset colorectal cancer (EOCRC) compared to late-onset colorectal cancer (LOCRC) through whole-genome sequencing (WGS) of both tissue and blood samples. The DAC is responsible for reviewing and approving access requests from researchers who wish to utilize this data for non-commercial, academic purposes related to colorectal cancer research. The committee ensures that all data access is granted in compliance with ethical standards and that the data is used solely for the approved research objectives. Researchers requesting access to this data must provide a detailed research proposal, institutional review board (IRB) approval, and demonstrate relevant expertise in genomic research. All data will be stored in secure, encrypted environments, and any further sharing or use of the data requires additional DAC approval.

  Dac EGAC50000000359

• Single-cell RNA sequencing reveals cell-type specific eQTLs in peripheral blood mononuclear cells

  This proof-of-concept study shows that single-cell RNA sequencing in ~25,000 peripheral blood mononuclear cells (PBMCs) of 45 donors allows for the identification of cell type-specific cis expression quantitative trait loci effects (cis-eQTLs). Moreover, the significant top-eQTL effects show consistent allelic direction (94%) with previously published whole blood deepSAGE data. These cell type-specific eQTLs may give us additional insight into the downstream consequences of genetic risk factors for immune-mediated diseases.

  Study EGAS00001002560

• Acral Melanoma PDXs from the admixed Brazilian Population- Human RNA expression data from Patient Derived Xenograft samples - htseq count files

  Files containing the read counts obtained with obtained with HTSeq for all the genes in Ensembl v103 annotation for GRCh38 human reference genome. This dataset contains the files for all the Patient Derived Xenograft samples. Counting was performed using filtered BAM files after the removal of mouse reads with XenofilteR. Acral melanoma (AM) is an aggressive melanoma subtype with limited therapeutic options and poor outcomes. In non-European descent and admixed populations, like in Latin America, it can account for a significant proportion of cutaneous melanoma cases. Here, we performed comprehensive genomic and functional profiling of AM from a uniquely diverse Brazilian cohort. Whole-exome and transcriptome sequencing was performed on both tumours and patient-derived xenograft (PDX) samples. The PDX were obtained from a comprehensive collection of patient-derived xenograft (AM-PDX) models that we established which faithfully retained the histopathological and genomic features of the original tumours.

  Dataset EGAD00001015747

• Genome-wide DNA methylation profiles of NSCLC xenograft and primary lung tissues for the identification of epigenetic predictive biomarkers.

  Non-small cell lung cancers (NSCLC) are the most common cause of cancer-related deaths worldwide and primarily treated with platinum-based drugs like cisplatin and carboplatin, radiation and surgery. The major challenge in the management of NSCLC are intrinsic or acquired resistance mechanisms with only few published molecular markers which can predict the outcome of the patients. On the other side, changes in DNA methylation are observed in nearly all cancer types making them suitable as biomarker. Here genome-wide methylation profiles from MeDIP-Seq and gene expression profiling data of 22 primary NSCLC, adjacent normal tissue and PDX samples are provided. For each PDX tumor growth rates were measured in absence or presence of chemotherapy.

  Study EGAS00001002479