Transcriptomic and regulatory landscape of liver tissue associated with meat and carcass quality traits in cattle

Abstract

The integration of multiple omics strategies represents a transformative paradigm in farm animal genetics and breeding. By capturing molecular complexity across biological layers, integrative omics offers new opportunities to reveal the regulatory mechanisms underlying economically important traits. Here, we characterize the hepatic transcriptomic landscape of Nelore cattle and its relationship with meat and carcass quality phenotypes. For that, we integrated gene expression data, co-expression networks, expression quantitative trait locus (eQTL) mapping, single-nucleotide polymorphism (SNP)–phenotype associations, chromatin accessibility, and transcription factor motif analyses using hepatic RNA-seq data from 90 animals and assay for transposase‑accessible chromatin using sequencing (ATAC-seq) data from two animals. Weighted gene co-expression network analysis (WGCNA) identified 10 gene modules associated with our phenotypes of interest, particularly the blue module (r = −0.4), which is linked to meat color and enriched in insulin and mTOR signaling pathways. eQTL mapping revealed 1,198 cis- and 39,227 trans-eQTLs (false discovery rate [FDR] < 0.05), including hotspots on chromosome 25. Notably, rs449155362 was found to regulate 848 genes, within them MLXIPL, a transcription factor involved in glucose and lipid metabolism. Phenotype–eQTL associations revealed 54 SNPs (FDR < 0.05) related to meat and carcass traits, among which rs110069409, within an open chromatin region, modulates PLA2G2D1 expression and was associated with meat color (yellowness 24 h after the slaughter—b*₀), representing a convergence point across regulatory layers. These findings provide novel insights into the multilayered genetic architecture of the liver that controls meat quality traits in beef cattle, supporting the use of integrative omics to guide functional genomic selection.