Gastrointestinal nematodes isotype-1 beta-tubulin and ITS2 deep amplicon sequencing from 6 cattle farms located in Buenos Aires province, Argentina

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dc.conicet.datoinvestigacionid26139
dc.conicet.justificacion
dc.conicet.linkAdjuntosigeva_files/POSTULANTE/27239078651/DATO/26121/Fastq_its2.7z
dc.conicet.linkAdjuntosigeva_files/POSTULANTE/27239078651/DATO/26121/Fastq-Btub.7z
dc.conicet.localizacionjson{"referencia":[{"id":"","nombre":"Buenos 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","tipo":"LUGAR","formato":"","latitud":"","longitud":"","puntosPoligonoList":[]}]}
dc.conicet.paisOrganizacionArgentina
dc.conicet.paisOrganizacionArgentina
dc.conicet.paisOrganizacionArgentina
dc.datacite.CreatorMaté, María Laura
dc.datacite.CreatorLiron, Juan Pedro
dc.datacite.CreatorCantón, Candela
dc.datacite.DateTypeRecolectado
dc.datacite.DescriptionTypeInformación Técnica
dc.datacite.FunderNameMinisterio de Ciencia. Tecnología e Innovación Productiva. Agencia Nacional de Promoción Científica y Tecnológica
dc.datacite.FundingReferencePICT-2020-00343
dc.datacite.PublicationYear2025*
dc.datacite.affiliationConsejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil
dc.datacite.affiliationConsejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil
dc.datacite.affiliationConsejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil
dc.datacite.awardTitleMONITOREO GENÉTICO DE LA RESISTENCIA ANTIHELMÍNTICA MEDIANTE SECUENCIACIÓN MASIVA DE AMPLICONES EN NEMATODOS GASTROINTESTINALES DEL BOVINO
dc.datacite.date1/4/2025
dc.datacite.descriptionBritish breed cattle and their crossbreeds, representative of the beef production systems in Buenos Aires province, Argentina, were used for fecal sampling over a period of approximately two years across six commercial farms operating under a grazing-based finishing system. The efficacy of BZDs and IVM in each commercial farm included in the project was previous to the feces sampling for isotype-1 b-tubulin analyses.In order to assess the molecular identification of GIN and determine the BZD resistance status of GIN parasitizing livestock, fecal samples from calves were collected between April 2020 and October 2021. The frequency of benzimidazole resistance alleles in parasitic nematodes communities was determined through deep amplicon sequencing of the isotype-1 b-tubulin and ITS2 genes, as previously described and detailed in Avramenko et al. (2019). The prepared pooled library was run on an Illumina Desktop Sequencer using a 500-cycle paired-end reagent kit (MiSeq Reagent Kit, v2, MS-103–2003) at a final concentration of 15 pM, with the addition of 25% PhiX control v3 (Illumina, FC-110-3001). The MiSeq was set to generate only FASTQ files.
dc.datacite.languageeng
dc.datacite.publisherConsejo Nacional de Investigaciones Científicas y Técnicas*
dc.datacite.resourceTypeGeneraldataset*
dc.datacite.subjectOtras Ciencias Veterinarias
dc.datacite.version1.0
dc.date.accessioned2025-04-03T09:06:04Z
dc.date.available2025-04-03T09:06:04Z
dc.date.updated2025-04-03T09:01:58Z
dc.description.abstractIn this study we applied the faecal egg count reduction test (FECRT), ITS2 and β-tubulin isotype 1 (β-tub-1) deep amplicon sequencing to assess, for the first time, the patterns of benzimidazole (BZD) resistance in gastrointestinal nematode (GIN) species infecting cattle from large-scale farms in Argentina subjected to different anthelmintic treatment strategies.
dc.description.filFil: Maté, María Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil; Argentina
dc.description.filFil: Liron, Juan Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil; Argentina
dc.description.filFil: Cantón, Candela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigación Veterinaria de Tandil. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigación Veterinaria de Tandil. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Centro de Investigación Veterinaria de Tandil; Argentina
dc.identifier.citationMaté, María Laura; Liron, Juan Pedro; Cantón, Candela; (2025): Gastrointestinal nematodes isotype-1 beta-tubulin and ITS2 deep amplicon sequencing from 6 cattle farms located in Buenos Aires province, Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. (dataset). http://hdl.handle.net/11336/257859*
dc.identifier.institucionalCONICET
dc.identifier.repoCONICET Digital
dc.identifier.urihttp://hdl.handle.net/11336/257859
dc.rightsinfo:eu-repo/semantics/openAccess*
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/*
dc.subject.keywordNEMABIOME
dc.subject.keywordISOTYPE-1 B-TUBULIN
dc.subject.keywordITS2 rDNA
dc.subject.keywordCATTLE
dc.subject.keywordPARASITES
dc.titleGastrointestinal nematodes isotype-1 beta-tubulin and ITS2 deep amplicon sequencing from 6 cattle farms located in Buenos Aires province, Argentina
dc.typedataset*

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ITS2 fastq paired end DNA sequences
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β-tub-1 bioinformatic workflow
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β-tub-1 database
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ITS2 bioinformatic workflow
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