Web of Science: 4 citations, Scopus: 4 citations, Google Scholar: citations,
Discovery and annotation of novel microRNAs in the porcine genome by using a semi-supervised transductive learning approach
Mármol-Sánchez, Emilio (Centre de Recerca en Agrigenòmica)
Cirera, Susanna (University of Copenhagen. Department of Veterinary and Animal Sciences (Denmark))
Quintanilla, Raquel (Institut de Recerca i Tecnologia Agroalimentàries)
Pla, Albert (University of Oslo. Department of Medical Genetics (Norway))
Amills i Eras, Marcel (Centre de Recerca en Agrigenòmica)

Date: 2020
Abstract: 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.
Grants: Ministerio de Economía y Competitividad SEV-2015-0533
Note: Altres ajuts: CERCA Programme/Generalitat de Catalunya
Rights: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Language: Anglès
Document: Article ; recerca ; Versió acceptada per publicar
Subject: MicroRNA discovery ; Motif search ; Porcine skeletal muscle ; Semi-supervised learning ; Small RNA-Seq
Published in: Genomics, Vol. 112, Issue 3 (May 2020) , p. 2107-2118, ISSN 1089-8646

DOI: 10.1016/j.ygeno.2019.12.005
PMID: 31816430


Postprint
53 p, 1.3 MB

Supplementary material
1.4 MB

The record appears in these collections:
Research literature > UAB research groups literature > Research Centres and Groups (research output) > Experimental sciences > CRAG (Centre for Research in Agricultural Genomics)
Articles > Research articles
Articles > Published articles

 Record created 2020-06-09, last modified 2022-09-23



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