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• The role of gut microbiota in metabolic diseases

  Diabetes is a major disease in the elderly and is responsible for increased risk of myocardial infarction and stroke. Recently, the relationship between microbiota and diabetes has been reported in animals and humans. In this study, blood, stool, and saliva samples were collected from examinees at the University of Tokyo Health Screening Center, and 16S rRNA and metagenomic analyses were performed to determine the variation of microbiota. Furthermore, metabolome analysis and transcriptome analysis (CAGE analysis) using blood were performed to reveal changes in host metabolites and gene expression. By comparing the host- and bacteria- derived information with the metabolic parameters, we analyzed whether microbiota can be a predictor of metabolic diseases.

  Study JGAS000569

• McGill Epigenomics Mapping Centre

  The McGill Epigenomics Mapping Centre (EMC) and Data Coordination Centre (EDCC) were established in 2012 at the McGill University and Genome Quebec Innovation Centre (Montreal, Canada) to support large-scale human epigenome mapping for a broad spectrum of cell types and diseases. Previous epigenetic studies have provided profiles of specific chromatin marks in relation to basic biological processes, and future studies of molecular mechanisms must build upon these proofs-of-concept by integrating sequence-based variation with multiple levels of epigenetic and transcriptional regulation across the genome of human tissues and animal disease models. This project leverages the high-throughput sequencing infrastructure and expertise in genomics and transcriptomics at the McGill Innovation Centre to carry out this research. Controlled access to the data by collaborators and the greater scientific community is gained via a portal, which takes advantage of Compute Canada high-performance computing cluster resources to manage the large volume of data associated from the generation of reference epigenome maps. McGill University is one of two Canadian mapping and data coordination centres, the other based at the Michael Smith Genome Sciences Centre in Vancouver, British Columbia. The generation of comprehensive epigenome maps at McGill University is part of a larger international effort that is coordinated by the International Human Epigenome Consortium (IHEC), whose overall long-term objective is to determine the extent to which the epigenome shapes human populations over generations and in response to the environment. This project is funded under the Canadian Epigenetics, Environment, and Health Research Consortium (CEEHRC) by the Canadian Institutes of Health Research and by Genome Quebec, with additional support from Genome Canada. The computing and networking infrastructure, and part of the software development, are provided by Compute Canada and CANARIE.

  Study EGAS00001000995

• Control samples, breast cancer clinical samples and matched patient-derived tumour xenografts (PDTXs) to develop and test a computational approach to discriminate human and mouse sequences in PDTXs

  Patient-Derived Tumour Xenografts (PDTXs) have emerged as the pre-clinical models that best represent clinical tumour diversity and intra-tumour heterogeneity. The molecular characterization of PDTXs using High-Throughput Sequencing (HTS) is essential; however, the presence of mouse stroma is challenging for HTS data analysis. Indeed, the high homology between the two genomes results in a proportion of mouse reads being mapped as human. In this study we generated Whole Exome Sequencing (WES) and RNA sequencing (RNA-seq) data from samples with known mixtures of mouse and human DNA or RNA.

  Study EGAS00001002445

• cell-free DNA Target sequencing from primary and recurrent/metastatic breast cancer patients

  Breast cancer is one of the most common cancers occurring worldwide in women. Even after curative treatment based on clinical subtypes according to molecular features, the risk of relapse still remains. Cell-free DNA (cfDNA) is an emerging tool for clinical cancer detection to monitor the risk of recurrence, therapeutic efficacy and tumor progression. In occurrence of relapse, genomic, transcriptomic and epigenetic profiles are altered, and reflected in cfDNA fragmentation patterns. In this study, we focus on the transcriptionally dynamic loci associated with therapy resistance in breast cancer, and develop the target sequencing approach using cfDNAs to detect individuals with recurrent/metastatic breast cancer.

  Study JGAS000812

• Gut 16S rRNA/FINRISK 2002

  The main goal of the project is the study the associations between the gut 16S rRNA and human health. The dataset contains data for FINRISK 2002 participants (a random sample of individuals living in six geographic areas in Finland) who underwent fecal sampling.

  Study EGAS50000000198

• NHLBI TOPMed: My Life Our Future (MLOF) Research Repository of Patients with Hemophilia A (Factor VIII Deficiency) or Hemophilia B (Factor IX Deficiency)

  Hemophilia A and B are X-linked bleeding disorders resulting from a deficiency in coagulation factor VIII (FVIII) or factor IX (FIX), respectively. Hemophilia affects approximately 1/5000 male births worldwide, and results in premature death and disability due to bleeding if coagulation factor replacement therapy is not used effectively. Hemophilia is clinically categorized by coagulation factor activity levels and ranges in severity from mild (6% to 30%) to moderate (1-5%) to severe (<1%). Many female "carriers" of hemophilia also have decreased factor activity and morbidity from bleeding. Hemophilia A and B are almost always caused by identifiable mutations in the F8 and F9 genes, respectively, and these mutations are found throughout the structural genes. Although the hemophilias are monogenic disorders, there are wide variations in disease severity and therapeutic outcomes which are not readily explained by the disease causing mutations alone. The My Life Our Future (MLOF) project (www.mylifeourfuture.org) is a national resource developed by a partnership of BloodworksNW (BWNW, formerly the Puget Sound Blood Center), the American Thrombosis and Hemostasis Network (ATHN), the National Hemophilia Foundation (NHF) and Bioverativ, to provide free F8 and F9 gene variant analysis to patients with hemophilia A or B, and to establish a research repository of DNA sequence, DNA, RNA, buffy coat, serum and plasma. The sequence analysis and serum samples are linked to a phenotypic database hosted by ATHN, with samples submitted and clinical data entered at ~100 hemophilia treatment centers (HTCs) nationwide. (See ATHN Research Report Brief in the resource center at www.athn.org). MLOF has become the largest hemophilia genetic project worldwide. The roles of the MLOF partners are: BWNW, to serve as the central laboratory for the project and house the research repository; ATHN, to support and provide the administrative link with HTCs, to facilitate the collection of accurate phenotypic data, to conduct research review and approval for use of the repository and with BWNW to provide samples and data for research projects; NHF, to provide consumer education and facilitate consumer input into the project; and Bioverativ, to provide financial support and scientific input. The project is governed by a Steering Committee consisting of one representative from each organization. Subject samples chosen from the MLOF parent study for TOPMed and WGS were drawn from those who gave (or parents gave) informed consent for the Research Repository and included patients of all severities and type, but with an emphasis on those with severe hemophilia and others at increased risk of neutralizing antibody (inhibitor) formation and who had samples in the Research Repository (plasma, serum, RNA) for potential additional -omic studies. Also included were samples from subjects where a likely causative variant for hemophilia was not found in the F8 or F9 coding region, intron-exon boundaries or immediate upstream and downstream regions. Since hemophilia is an X-linked disorder, the majority of subjects are male. Racial distribution is similar to the overall population distribution.

  Study phs001515

• Detecting and Subtyping Lung Cancer Through Analysis of Circulating Tumor DNA

  Small cell lung cancer (SCLC) is among the most aggressive tumors with poor clinical outcomes. Tumors are rarely resected, which is a major barrier to molecular profiling of tumor tissue; therefore, non-invasive approaches using circulating tumor DNA (ctDNA) from liquid biopsies are needed to help advance research and clinical care for patients with SCLC. We developed a targeted capture panel that profiles SCLC genes and transcriptional regulation sites, including transcription start sites (TSS) and transcription factor binding sites (TFBS). This is a single assay that detects genomic mutations and transcriptional regulation activity based on ctDNA fragment patterns reflecting epigenetic nucleosomal positions. We applied this assay to sequence patient-derived xenograft (PDX) and patient plasma samples. We also performed whole genome sequencing (WGS) for a subset of the PDX plasma samples to validate the capture data. We developed new algorithms to quantify activity of key SCLC marker genes of ASCL1, NEUROD1, POU2F3, and ATOH1 and to classify SCLC subtypes based on activity of these markers. Furthermore, we developed a model to classify SCLC from non-small cell lung cancer (NSCLC), which has potential important applications for monitoring transdifferentiation and tumor plasticity.

  Study phs003570

• Spatial Transcriptomics on prostate cancer heterogeneity

  Intratumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology. Utilizing a novel approach for deconvolution, we analyze the transcriptomes of nearly 6750 tissue regions and extract distinct expression profiles for the different tissue components, such as stroma, normal and PIN glands, immune cells and cancer. We distinguish healthy and diseased areas and thereby provide insight into gene expression changes during the progression of prostate cancer. Compared to pathologist annotations, we delineate the extent of cancer foci more accurately, interestingly without link to histological changes. We identify gene expression gradients in stroma adjacent to tumor regions that allow for re-stratification of the tumor microenvironment. The establishment of these profiles is the first step towards an unbiased view of prostate cancer and can serve as a dictionary for future studies.

  Study EGAS00001003001

• Rapid Evolution of a Skin Lightening Allele in Southern African KhoeSan

  The genetic architecture and polygenicity of skin pigmentation is explored in KhoeSan communities, including Nama individuals whose phenotype and genotype data are provided in this dataset. By pairing genotypes and quantitative spectrophotometric skin pigmentation phenotypes, we show that skin pigmentation is highly heritable in KhoeSan, yet known pigmentation loci only explains a small fraction of the phenotypic variance. Using genome-wide association analyses, we identified both canonical and non-canonical skin pigmentation loci. We show that this phenotype is more polygenic and complex than previously characterized. (Martin et al., Cell 2017. PMID: 29195075) Following up on the top associated signal with large effect size in the gene SLC24A5, we demonstrate that the canonical Eurasian nonsynonymous allele was introduced into KhoeSan via a recent migration ~2 kya and was under extremely strong selection. The derived allele was present at high frequency despite controlling for gene flow. With high-throughput sequences in the captured SLC24A5 region, we show that the most common derived haplotype is identical amongst Europeans, eastern African and KhoeSan. Using 4-population demographic simulations with selection, we show that the allele was introduced into the KhoeSan only 2,000 ya via a back-to-Africa migration and then experienced a selective sweep.

  Study phs001753

• Joint Addiction, Aging, and Mental Health (JAAMH) Data Access Committee General Research Use Datasets

  This collection contains all the Joint Addiction, Aging, and Mental Health (JAAMH) Data Access Committee General Research Use Datasets authorized individual-level genomic datasets currently in dbGaP that are approved for General Research Use (GRU) and have no further limitations beyond those outlined in the model Data Use Certification Agreement. The public posting of Genomic Summary Results is allowed. Access to this study collection will include additional authorized individual-level GRU datasets that become available. Renewal of this study collection is required annually. To request access to this study collection, select phs003202 in the dbGaP Authorized Access System.

  Study phs003202