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dc.contributor.authorMármol-Sánchez, Emilio
dc.contributor.authorCirera, Susanna
dc.contributor.authorQuintanilla, Raquel
dc.contributor.authorPla, Albert
dc.contributor.authorAmills, Marcel
dc.contributor.otherProducció Animalca
dc.date.accessioned2020-05-26T05:58:45Z
dc.date.issued2019-12-06
dc.identifier.citationMármol-Sánchez, Emilio, Susanna Cirera, Raquel Quintanilla, Albert Pla, and Marcel Amills. 2020. "Discovery And Annotation Of Novel Micrornas In The Porcine Genome By Using A Semi-Supervised Transductive Learning Approach". Genomics 112 (3): 2107-2118. Elsevier BV. doi:10.1016/j.ygeno.2019.12.005.ca
dc.identifier.issn0888-7543ca
dc.identifier.urihttp://hdl.handle.net/20.500.12327/822
dc.description.abstractDespite the broad variety of available microRNA (miRNA) prediction tools, their application to the discovery and annotation of novel miRNA genes in domestic species is still limited. In this study we designed a comprehensive pipeline (eMIRNA) for miRNA identification in the yet poorly annotated porcine genome and demonstrated the usefulness of implementing a motif search positional refinement strategy for the accurate determination of precursor miRNA boundaries. The small RNA fraction from gluteus medius skeletal muscle of 48 Duroc gilts was sequenced and used for the prediction of novel miRNA loci. Additionally, we selected the human miRNA annotation for a homology-based search of porcine miRNAs with orthologous genes in the human genome. A total of 20 novel expressed miRNAs were identified in the porcine muscle transcriptome and 27 additional novel porcine miRNAs were also detected by homology-based search using the human miRNA annotation. The existence of three selected novel miRNAs (ssc-miR-483, ssc-miR484 and ssc-miR-200a) was further confirmed by reverse transcription quantitative real-time PCR analyses in the muscle and liver tissues of Göttingen minipigs. In summary, the eMIRNA pipeline presented in the current work allowed us to expand the catalogue of porcine miRNAs and showed better performance than other commonly used miRNA prediction approaches. More importantly, the flexibility of our pipeline makes possible its application in other yet poorly annotated non-model species.ca
dc.format.extent53ca
dc.language.isoengca
dc.publisherElsevierca
dc.relation.ispartofGenomicsca
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalca
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleDiscovery and annotation of novel microRNAs in the porcine genome by using a semi-supervised transductive learning approachca
dc.typeinfo:eu-repo/semantics/articleca
dc.description.versioninfo:eu-repo/semantics/acceptedVersionca
dc.rights.accessLevelinfo:eu-repo/semantics/embargoedAccess
dc.date.embargoEnd2020-12-05T01:00:00Z
dc.embargo.terms12 mesosca
dc.relation.projectIDMINECO/Programa Estatal de I+D+I orientada a los retos de la sociedad/AGL2013-48742-C2-1-R/ES/FISIOLOGIA GENOMICA DEL DEPOSITO DE GRASA INTRAMUSCULAR EN PORCINO/ca
dc.relation.projectIDMINECO/Programa Estatal de I+D+I orientada a los retos de la sociedad/AGL2013-48742-C2-2-R/ES/FISIOLOGIA GENOMICA DEL DEPOSITO DE GRASA INTRAMUSCULAR EN PORCINO/ca
dc.relation.projectIDMINECO/Programa Estatal de fomento de la investigación científica y técnica de excelencia/SEV-2015-0533/ES/ /ca
dc.subject.udc63ca
dc.identifier.doihttps://doi.org/10.1016/j.ygeno.2019.12.005ca
dc.contributor.groupGenètica i Millora Animalca


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