Abstract
Long non-coding RNAs (lncRNAs) can influence transcriptional and translational processes in mammalian cells and are associated with various developmental, physiological and phenotypic conditions. However, they remain poorly understood and annotated in livestock species. We combined phenotypic, metabolomics and liver transcriptomic data of bulls divergent for residual feed intake (RFI) and fat accretion. Based on a project-specific transcriptome annotation for the bovine reference genome ARS-UCD.1.2 and multiple-tissue total RNA sequencing data, we predicted 3590 loci to be lncRNAs. To identify lncRNAs with potential regulatory influence on phenotype and gene expression, we applied the regulatory impact factor algorithm on a functionally prioritized set of loci (n = 4666). Applying the algorithm of partial correlation and information theory, significant and independent pairwise correlations were calculated and co-expression networks were established, including plasma metabolites correlated with lncRNAs. The network hub lncRNAs were assessed for potential cis-actions and subjected to biological pathway enrichment analyses. Our results reveal a prevalence of antisense lncRNAs positively correlated with adjacent protein-coding genes and suggest their participation in mitochondrial function, acute phase response signalling, TCA-cycle, fatty acid β-oxidation and presumably gluconeogenesis. These antisense lncRNAs indicate a stabilizing function for their cis-correlated genes and a putative regulatory role in gene expression.
Highlights
While the functionality of protein-coding genes has been thoroughly explored and scrutinized in the past century—and continues to be—the so-called ‘dark matter of the genome’ has shifted into focus in the recent decades
In a locus-based approach, where we considered the transcript with the highest exon number for each long non-coding RNAs (lncRNAs) locus, we observed that strandedness was distributed among the 3590 loci (50.84% on the plus and 49.16% on the minus strand)
Using the bioinformatics lncRNA prediction tool FEELnc [22], which has been applied to determine lncRNAs in different species, including dogs [44], chicken [45], cattle [30,36] and pigs [46], we have identified 3590 lncRNA loci expressed in the liver transcriptome
Summary
While the functionality of protein-coding genes has been thoroughly explored and scrutinized in the past century—and continues to be—the so-called ‘dark matter of the genome’ has shifted into focus in the recent decades. Numerous association studies have aimed to find causative genomic regions and gene variants that drive bovine feed efficiency, but repeatedly quantitative trait locus (QTL) peaks fall outside the protein-coding genes, e.g., [4,5,6,7]. This plethora of work suggests that the functional tasks of the non-coding elements affecting feed efficiency need to be addressed in greater detail
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