Competing endogenous RNA network construction based on long non-coding RNAs, microRNAs, and mRNAs related to fat deposition in Songliao black swine.

Abstract

China has a long history of pig breeding and a number of local breeds. The Songliao Black pig, bred in China in 2009, shows high variation in backfat thickness and therefore is well-suited to fat deposition research. Fat deposition is a complex trait, and the underlying regulatory factors are not fully characterized. In this study, the molecular basis of fat deposition traits was evaluated by comparisons between three individuals with extremely high-backfat thickness and three with extremely low-backfat thickness selected from 53 gilts. Subcutaneous adipose tissues of the back were collected for strand-specific library RNA sequencing (RNA-seq) and small RNA-seq. We identified 13 184 mRNAs, 2046 long non-coding (lnc)RNAs, and 494 micro (mi)RNAs by high-throughput sequencing. Furthermore, we detected 150 differentially expressed mRNAs, 66 differentially expressed lncRNAs, and eight differentially expressed miRNAs. A functional enrichment analysis indicated that these genes are involved in multiple fat metabolism-related pathways, including positive regulation of fat cell differentiation, and fat digestion and absorption. We used various algorithms (miRanda, TargetScan, and RNAhybrid) to predict targeting relationships and constructed a competing endogenous RNA network containing seven lncRNAs, three miRNAs, and six mRNAs. All these genes were differentially expressed between the extremely high and low backfat thickness groups or enriched in pathways related to fat metabolism. Our results provide insight into the regulatory mechanisms by which non-coding RNAs and their target genes influence backfat deposition in pigs. Furthermore, our newly constructed competing endogenous RNA (lncRNA-miRNA-mRNA) network provides a basis for further exploration of fat deposition traits and non-coding RNA functions.