lncRNA_cattle_FAANG
Biological network approach for the identification of regulatory long non-coding RNAs associated with metabolic efficiency in cattle
Genomic regions associated with divergent livestock feed efficiency have been found predominantly outside protein coding sequences. Long non-coding RNAs (lncRNA) can modulate chromatin accessibility, gene expression and are supposed to act as important metabolic regulators in mammals. By integrating phenotypic, transcriptomic and metabolomic data with QTL data in prioritizing co-expression network analyses, we aimed to identify and functionally characterize lncRNAs with a potential key regulatory role in metabolic efficiency in cattle. Crossbred animals (n = 48) of a Charolais x Holstein F2-population were allocated to groups of high or low metabolic efficiency based on residual feed intake (RFI) in bulls, energy corrected milk in cows and intramuscular fat content in both genders. Tissue samples from jejunum, liver, skeletal, muscle and rumen were subjected to global transcriptomic analysis via stranded total RNA sequencing (RNAseq) and blood plasma samples were used for profiling of 640 metabolites. To identify lncRNAs within the indicated tissues, a project-specific transcriptome annotation was established. Subsequently, novel annotated transcripts were categorized for potential lncRNA status, yielding a total of 7,646 predicted lncRNA transcripts belonging to 3,287 loci. The ensuing regulatory impact factor (RIF) approach attributed a significant RIF score to 92, 55, 35, and 73 lncRNAs in jejunum, liver, muscle, and rumen, respectively. This indicates their high regulatory potential for a gene set comprising loci displaying differential expression, tissue specificity and loci overlapping with QTL regions for RFI or milk production. These were subjected to a partial correlation and information theory (PCIT) analysis with the prioritized gene set. Independent, significant and group-specific correlations (|r| > 0.8) were used to build a network for the high and the low metabolic efficiency group resulting in 1,522 and 1,732 nodes, respectively. Eight lncRNAs displayed a particularly high connectivity (> 100 nodes). Metabolites and genes from the PCIT networks, which each correlated significantly with the respective lncRNA, were included in an enrichment analysis indicating distinct affected pathways for the eight lncRNAs. LncRNAs associated with metabolic efficiency seemed to be functionally involved in hepatic amino acid metabolism and protein synthesis and in calcium signaling and nNOS signaling in skeletal muscle cells.