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Discovery and annotation of novel microRNAs in the porcine genome by using a semi-supervised transductive learning approach.

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.

journal_name

Genomics

journal_title

Genomics

authors

Mármol-Sánchez E,Cirera S,Quintanilla R,Pla A,Amills M

doi

10.1016/j.ygeno.2019.12.005

subject

Has Abstract

pub_date

2020-05-01 00:00:00

pages

2107-2118

issue

3

eissn

0888-7543

issn

1089-8646

pii

S0888-7543(19)30488-4

journal_volume

112

pub_type

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