{ "resources": [ { "name": "cov_pmv_wdds", "path": "cov_pmv_wdds.csv", "profile": "tabular-data-resource", "format": "csv", "mediatype": "text/csv", "encoding": "UTF-8", "schema": { "fields": [ { "name": "animalID", "type": "number", "description": "A researcher-generated unique ID for the individual animal from which the sample was collected: usually a unique string of both characters and integers (e.g., BZ19-114 to indicate animal 114 sampled in 2019 in Belize). Ideally, animal names should again be kept consistent across online databases and physical resources." }, { "name": "collectionNumber", "type": "string", "description": "An identifier given to the dwc:Occurrence at the time it was recorded. Often serves as a link between field notes and a dwc:Occurrence record, such as a specimen collector's number. http://rs.tdwg.org/dwc/terms/recordNumber" }, { "name": "hostIdentification", "type": "string", "description": "The Linnaean classification of the animal from which the sample was collected, reported at the lowest possible level (ideally, species binomial name: e.g., Odocoileus virginianus or Ixodes scapularis). As necessary, researchers may also include an additional field indicating when uncertainty exists in the identification of the host organism (see Adding new fields). See http://rs.tdwg.org/dwc/terms/scientificName" }, { "name": "country", "type": "string", "description": "The name of the country or major administrative unit in which the dcterms:Location occurs. http://rs.tdwg.org/dwc/terms/country" }, { "name": "locality", "type": "string", "description": "The specific description of the place. http://rs.tdwg.org/dwc/terms/locality" }, { "name": "latitude", "type": "number", "description": "Latitude of the collection site in decimal format. See http://rs.tdwg.org/dwc/terms/decimalLatitude" }, { "name": "longitude", "type": "number", "description": "Longitude of the collection site in decimal format. See http://rs.tdwg.org/dwc/terms/decimalLongitude" }, { "name": "collectionYear", "type": "number", "description": "The year in which the specimen was collected. See http://rs.tdwg.org/dwc/terms/year" }, { "name": "sampleMaterial", "type": "string", "description": "Organic tissue or fluid being collected (e.g., “liver”; “blood”; “skin”; “whole organism”)." }, { "name": "storageMedium", "type": "string", "description": "A data field which describes the material or matrix in which a sample is stored http://purl.obolibrary.org/obo/GENEPIO_0100449" }, { "name": "modelPrediction", "type": "string", "description": "predicted host status based on machine learning model in 'Museum collections and machine learning guide discovery of novel coronaviruses and paramyxoviruses'" }, { "name": "detectionOutcome", "type": "string", "description": "The test result (i.e., positive, negative, or inconclusive). To avoid ambiguity, these specific values are suggested over numeric values (0 or 1). See http://rs.tdwg.org/dwc/terms/occurrenceStatus" }, { "name": "parasiteIdentification", "type": "string", "description": "The identity of a parasite detected by the test, if any, reported to the lowest possible taxonomic level, either as a Linnaean binomial classification or within the convention of a relevant taxonomic authority (e.g., Borrelia burgdorferi or Zika virus). Parasite identification may be more specific than detection target." }, { "name": "genbankAccession", "type": "string", "description": "" }, { "name": "notes", "type": "string", "description": "additional information on taxonomy, infection, and sequence length." }, { "name": "sampleCollectionMethod", "type": "string", "description": "The technique used to acquire the sample and/or the tissue from which the sample was acquired (e.g. visual inspection; swab; wing punch; necropsy)." }, { "name": "detectionMethod", "type": "string", "description": "The type of test performed to detect the parasite or parasite-specific antibody (e.g., 'qPCR', ‘ELISA’)" }, { "name": "geneTarget", "type": "string", "description": "The parasite gene targeted by the primer (e.g. “RdRp” for PCR.)." }, { "name": "primerCitation", "type": "string", "description": "Citation(s) for the primer(s) (ideally doi, or other permanent identifier for a work, e.g. PMID). " }, { "name": "detectionTarget", "type": "string", "description": "The taxonomic identity of the parasite being screened for in the sample. This will often be coarser than the identity of a specific parasite identified in the sample: for example, in a study screening for novel bat coronaviruses, the entire family Coronaviridae might be the target; in a parasite dissection, the targets might be Acanthocephala, Cestoda, Nematoda, and Trematoda. For deep sequencing approaches (e.g., metagenomic and metatranscriptomic viral discovery), researchers should report each alignment target used as a new test to maximize reporting of negative data, or alternatively, select a subset that reflect specific study objectives and the focus of analysis (e.g., specific viral families). See http://rs.tdwg.org/dwc/terms/associatedOccurrences" }, { "name": "sampleID", "type": "string", "description": "A researcher-generated unique ID for the sample: usually a unique string of both characters and integers (e.g., OS BZ19-114 to indicate an oral swab taken from animal BZ19-114; see worked example below), to avoid conflicts that can arise when datasets are merged with number-only notation for samples. Ideally, sample names should be kept consistent across all online databases and physical resources (e.g., museum collections or project-specific sample archives)." } ] } }, { "name": "fmnh244607_fmnh244565", "path": "fmnh244607_fmnh244565.fasta", "profile": "tabular-data-resource", "format": "csv", "mediatype": "text/csv", "encoding": "UTF-8", "schema": { "fields": [ { "name": ">FMNH244607_G_humeralis_paramyxovirus", "type": "string" } ] } }, { "name": "project_metadata", "path": "project_metadata.json", "profile": "tabular-data-resource", "format": "csv", "mediatype": "text/csv", "encoding": "UTF-8", "schema": { "fields": [ { "name": "{", "type": "string" } ] } }, { "name": "cov_alignment", "path": "cov_alignment.fasta", "profile": "tabular-data-resource", "format": "csv", "mediatype": "text/csv", "encoding": "UTF-8", "schema": { "fields": [ { "name": ">OR482618.1 Gammacoronavirus sp. isolate AvCoV/spot-billed duck/Primorie/M3773/2021 RdRp (ORF1ab) gene", "type": "string" }, { "name": " partial cds", "type": "string" } ] } }, { "name": "pmv_alignment", "path": "pmv_alignment.fasta", "profile": "tabular-data-resource", "format": "csv", "mediatype": "text/csv", "encoding": "UTF-8", "schema": { "fields": [ { "name": ">Menangle pararubulavirus (AF326114)", "type": "string" } ] } } ], "metadata": { "accessRights": "open", "created": "2025-09-08", "creator": [ { "name": "Maya M. Juman", "affiliation": "https://ror.org/013meh722", "orcid": "https://orcid.org/0000-0002-0211-0655" }, { "name": "Bruce D. Patterson", "affiliation": "https://ror.org/00mh9zx15", "orcid": "https://orcid.org/0000-0002-2249-7260" }, { "name": "Greg F. Albery", "affiliation": "https://ror.org/02tyrky19", "orcid": "https://orcid.org/0000-0001-6260-2662" }, { "name": "Colin J. Carlson", "affiliation": "https://ror.org/03v76x132", "orcid": "https://orcid.org/0000-0001-6960-8434" }, { "name": "Daniel J. Becker", "affiliation": "https://ror.org/02aqsxs83", "orcid": "https://orcid.org/0000-0003-4315-8628" }, { "name": "Molly M. McDonough", "affiliation": "https://ror.org/05ekwbr88", "orcid": "https://orcid.org/0000-0002-4890-7993" }, { "name": "Adam W. Ferguson", "affiliation": "https://ror.org/00mh9zx15", "orcid": "https://orcid.org/0000-0002-6931-6420" }, { "name": "Barbara A. Han", "affiliation": "https://ror.org/01dhcyx48", "orcid": "https://orcid.org/0000-0002-9948-3078" }, { "name": "Frank Bapeamoni Andemwana", "affiliation": "https://ror.org/028svp844", "orcid": "https://orcid.org/0000-0003-1079-9189" }, { "name": "Bertin Murhabale Cisirika", "affiliation": "https://ror.org/02pad2v09" }, { "name": "Charles Kahindo", "affiliation": "https://ror.org/02pad2v09" }, { "name": "Luis M.P. Ceríaco", "affiliation": "https://ror.org/0476hs695", "orcid": "https://orcid.org/0000-0002-0591-9978" }, { "name": "Steven M. Goodman", "affiliation": "https://ror.org/00mh9zx15", "orcid": "https://orcid.org/0000-0001-9318-0570" } ], "description": "Tissue samples from specimens at the Field Museum of Natural History screened for coronavirus (n = 1330) and paramyxovirus (n = 491) RNA by RT-PCR. Natural history museum collections are valuable but underutilized resources for viral discovery, offering opportunities to test hypotheses about viral occurrence across space, time, and taxonomic groups. We developed machine learning models of bat host suitability to guide coronavirus and paramyxovirus screening of 1330 and 491 archival tissues, respectively, in a museum collection. For the first time, we recovered coronavirus (n = 16) and paramyxovirus (n = 3) sequences from museum tissues, confirming three novel coronavirus host species and three novel paramyxovirus host species (3% and 33% prediction success rate, respectively). These sequences included a SARS-like coronavirus and an orthoparamyxovirus from Angolan Rhinolophus fumigatus specimens collected in June 2019, suggesting that viruses with epidemic potential may be more widespread in sub-Saharan Africa than previously believed. Our study demonstrates the value of combining predictive modeling and collections-based viral discovery, particularly for filling outstanding sampling gaps and investigating changes in host–virus associations over time. \nThe data in this deposit are structured as a frictionless data pacakge (https://datapackage.org/standard/data-package/).\nThe datapackage.json file contains descriptive metadata (i.e. metadata related to the project) and structural metadata (i.e. metadata descrbing the structure and contents of the data).\nThis means that field descriptions can be found in the datapackage.json file.\n\nCoronavirus and Paramyxovirus data are stored in cov_pmv_wdds.csv.\n\nThe project_metadata.json file contains richer project metadata.\n\nBoth the data and metadata conform to the Wildlife Disease Data Standard version 1.0.3. ** Some sequence data did not meet genbank criteria for deposition. See fasta files. \nThe data in this deposit are structured as a frictionless data pacakge (https://datapackage.org/standard/data-package/).\nThe datapackage.json file contains descriptive metadata (i.e. metadata related to the project) and structural metadata (i.e. metadata descrbing the structure and contents of the data).\nThis means that field descriptions can be found in the datapackage.json file.\n\nCoronavirus and Paramyxovirus data are stored in cov_pmv_wdds.csv.\n\nThe project_metadata.json file contains richer project metadata.\n\nBoth the data and metadata conform to the Wildlife Disease Data Standard version 1.0.3.\n\nSome sequence data did not meet genbank criteria for deposition. See fmnh244607_fmnh244565.fasta for those sequences.\n\nAlignement data for cov and pmv can be found in *_alignment.fasta", "language": "en", "license": "cc-by", "relation": [ { "identifier": "https://github.com/viralemergence/fnmh_cov_pmv_to_wdds/", "relation": "hasPart" }, { "identifier": "https://doi.org/10.5281/zenodo.15270582", "relation": "isDescribedBy" } ], "title": "Museum collections and machine learning guide discovery of novel coronaviruses and paramyxoviruses" } }