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      Multi-omics approach identifies germline regulatory variants associated with hematopoietic malignancies in retriever dog breeds

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          Abstract

          Histiocytic sarcoma is an aggressive hematopoietic malignancy of mature tissue histiocytes with a poorly understood etiology in humans. A histologically and clinically similar counterpart affects flat-coated retrievers (FCRs) at unusually high frequency, with 20% developing the lethal disease. The similar clinical presentation combined with the closed population structure of dogs, leading to high genetic homogeneity, makes dogs an excellent model for genetic studies of cancer susceptibility. To determine the genetic risk factors underlying histiocytic sarcoma in FCRs, we conducted multiple genome-wide association studies (GWASs), identifying two loci that confer significant risk on canine chromosomes (CFA) 5 ( P wald = 4.83x10 -9) and 19 ( P wald = 2.25x10 -7). We subsequently undertook a multi-omics approach that has been largely unexplored in the canine model to interrogate these regions, generating whole genome, transcriptome, and chromatin immunoprecipitation sequencing. These data highlight the PI3K pathway gene PIK3R6 on CFA5, and proximal candidate regulatory variants that are strongly associated with histiocytic sarcoma and predicted to impact transcription factor binding. The CFA5 association colocalizes with susceptibility loci for two hematopoietic malignancies, hemangiosarcoma and B-cell lymphoma, in the closely related golden retriever breed, revealing the risk contribution this single locus makes to multiple hematological cancers. By comparison, the CFA19 locus is unique to the FCR and harbors risk alleles associated with upregulation of TNFAIP6, which itself affects cell migration and metastasis. Together, these loci explain ~35% of disease risk, an exceptionally high value that demonstrates the advantages of domestic dogs for complex trait mapping and genetic studies of cancer susceptibility.

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          We have identified two regions of the canine genome that explain a striking 35% of risk for developing histiocytic sarcoma in FCRs. The disease is uniformly lethal, affects 20% of FCRs, and parallels a cancer of the same name in humans. Both regions harbor genes involved in cell migration and cancer-related pathways. The first includes variants in regulatory regions at the tumor suppressor PIK3R6 locus that are strongly associated with histiocytic sarcoma and likely confer risk for other hematopoietic cancers. FCRs with risk alleles at the second locus demonstrate increased expression of TNFAIP6, which correlates with poor prognosis in multiple human cancers. In identifying genomic differences between affected and unaffected dogs, we advance our understanding of both canine and human health biology and set the stage for the development of diagnostic and therapeutic strategies.

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          Most cited references53

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Integrative analysis of 111 reference human epigenomes

            The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but a similar reference has lacked for epigenomic studies. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection to-date of human epigenomes for primary cells and tissues. Here, we describe the integrative analysis of 111 reference human epigenomes generated as part of the program, profiled for histone modification patterns, DNA accessibility, DNA methylation, and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically-relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation, and human disease.
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              FIMO: scanning for occurrences of a given motif

              Summary: A motif is a short DNA or protein sequence that contributes to the biological function of the sequence in which it resides. Over the past several decades, many computational methods have been described for identifying, characterizing and searching with sequence motifs. Critical to nearly any motif-based sequence analysis pipeline is the ability to scan a sequence database for occurrences of a given motif described by a position-specific frequency matrix. Results: We describe Find Individual Motif Occurrences (FIMO), a software tool for scanning DNA or protein sequences with motifs described as position-specific scoring matrices. The program computes a log-likelihood ratio score for each position in a given sequence database, uses established dynamic programming methods to convert this score to a P-value and then applies false discovery rate analysis to estimate a q-value for each position in the given sequence. FIMO provides output in a variety of formats, including HTML, XML and several Santa Cruz Genome Browser formats. The program is efficient, allowing for the scanning of DNA sequences at a rate of 3.5 Mb/s on a single CPU. Availability and Implementation: FIMO is part of the MEME Suite software toolkit. A web server and source code are available at http://meme.sdsc.edu. Contact: t.bailey@imb.uq.edu.au; t.bailey@imb.uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: InvestigationRole: MethodologyRole: Resources
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: InvestigationRole: Resources
                Role: Data curation
                Role: Resources
                Role: ConceptualizationRole: Funding acquisitionRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Genet
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, CA USA )
                1553-7390
                1553-7404
                13 May 2021
                May 2021
                : 17
                : 5
                : e1009543
                Affiliations
                [1 ] Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
                [2 ] Department of Clinical Sciences, division Internal Medicine of Companion Animals, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
                [3 ] Department Biomedical Health Sciences, division Pathology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
                [4 ] College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, Colorado, United States of America
                Translational Genomics Research Institute, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-1272-0059
                https://orcid.org/0000-0002-9707-6380
                https://orcid.org/0000-0002-2112-1595
                https://orcid.org/0000-0002-1583-9648
                https://orcid.org/0000-0002-6868-5363
                Article
                PGENETICS-D-21-00048
                10.1371/journal.pgen.1009543
                8118335
                33983928
                67de446b-080a-4f93-b73c-c8be3b92b8dc

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 13 January 2021
                : 12 April 2021
                Page count
                Figures: 5, Tables: 3, Pages: 20
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000051, National Human Genome Research Institute;
                Funded by: UK Flatcoated Retriever Society
                Funded by: funder-id http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: 1FI2GM133344-01
                Award Recipient :
                Funded by: Flint Animal Cancer Center
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000780, European Commission;
                Award ID: LUPA-GA-201370
                Award Recipient :
                This work was supported by the Intramural Program of the National Human Genome Research Institute at NIH ( https://www.genome.gov/) with partial support from the UK Flatcoated Retriever Society ( https://www.flatcoated-retriever-society.org/). JME was supported by a National Institute of General Medical Sciences Postdoctoral Research Associate Training fellowship, award number 1FI2GM133344-01 ( https://www.nigms.nih.gov/training/pages/prat.aspx). SEL was funded by The Flint Animal Cancer Center ( https://www.csuanimalcancercenter.org/). GRR was partially funded by European Commission, grant number LUPA-GA-201370 ( https://ec.europa.eu). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Epidemiology
                Medical Risk Factors
                Cancer Risk Factors
                Medicine and Health Sciences
                Oncology
                Cancer Risk Factors
                Biology and Life Sciences
                Genetics
                Heredity
                Genetic Mapping
                Haplotypes
                Medicine and Health Sciences
                Oncology
                Cancers and Neoplasms
                Sarcoma
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Genome-Wide Association Studies
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Genome-Wide Association Studies
                Biology and Life Sciences
                Genetics
                Human Genetics
                Genome-Wide Association Studies
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Mammals
                Dogs
                Biology and Life Sciences
                Zoology
                Animals
                Vertebrates
                Amniotes
                Mammals
                Dogs
                Medicine and Health Sciences
                Oncology
                Cancers and Neoplasms
                Hematologic Cancers and Related Disorders
                Lymphoma
                Medicine and Health Sciences
                Hematology
                Hematologic Cancers and Related Disorders
                Lymphoma
                Biology and Life Sciences
                Genetics
                Genetic Loci
                Biology and Life Sciences
                Genetics
                Genomics
                Animal Genomics
                Mammalian Genomics
                Custom metadata
                SRA accession numbers for WGS are in S8 Table. RNA-seq and ChIP-seq data are in SRA (PRJNA685036). SNP chip data are in GEO (GSE163784). Remaining relevant data are within the manuscript and Supporting Information files.

                Genetics
                Genetics

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