Discovery and annotation of novel microRNAs in the porcine genome by using a semi-supervised transductive learning approach
Ver/Abrir
Fecha de publicación
2019-12-06ISSN
0888-7543
Resumen
Despite 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.
Tipo de documento
Artículo
Versión del documento
Versión aceptada
Lengua
English
Materias (CDU)
63 - Agricultura. Silvicultura. Zootecnia. Caza. Pesca
Páginas
53
Publicado por
Elsevier
Publicado en
Genomics
Citación
Mármol-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.
Número del acuerdo de la subvención
MINECO/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/
MINECO/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/
MINECO/Programa Estatal de fomento de la investigación científica y técnica de excelencia/SEV-2015-0533/ES/ /
Program
Genètica i Millora Animal
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