Multi-omics analysis
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. We integrated gene expression, co-expression networks, eQTL mapping, SNP–phenotype associations, chromatin accessibility, and transcription factor motif analyses using hepatic RNA-seq data from 90 animals and ATAC-seq data from 2 animals. Weighted Gene Co-expression Network Analysis identified ten modules associated with phenotypes, particularly the blue module (R = –0.4) linked to meat color and enriched in insulin and mTOR signaling pathways. eQTL mapping revealed 1,198 cis- and 39,227 trans-eQTLs (FDR < 0.05), including hotspots on chromosome 25. Notably, rs449155362 regulates 848 genes, including MLXIPL, a transcription factor involved in glucose and lipid metabolism. Phenotype–eQTL associations highlighted 54 SNPs (FDR < 0.05) related to meat and carcass traits, among which rs110069409 within an open chromatin region modulates PLA2G2D3 expression and meat color (yellowness 24 hours after the slaughter- b*0), representing a convergence point across regulatory layers. These findings provide novel insights into the multilayered genetic architecture controlling meat quality traits in beef cattle, supporting the use of integrative omics to guide functional genomic selection
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. We integrated gene expression, co-expression networks, eQTL mapping, SNP–phenotype associations, chromatin accessibility, and transcription factor motif analyses using hepatic RNA-seq data from 90 animals and ATAC-seq data from 2 animals. Weighted Gene Co-expression Network Analysis identified ten modules associated with phenotypes, particularly the blue module (R = –0.4) linked to meat color and enriched in insulin and mTOR signaling pathways. eQTL mapping revealed 1,198 cis- and 39,227 trans-eQTLs (FDR < 0.05), including hotspots on chromosome 25. Notably, rs449155362 regulates 848 genes, including MLXIPL, a transcription factor involved in glucose and lipid metabolism. Phenotype–eQTL associations highlighted 54 SNPs (FDR < 0.05) related to meat and carcass traits, among which rs110069409 within an open chromatin region modulates PLA2G2D3 expression and meat color (yellowness 24 hours after the slaughter- b*0), representing a convergence point across regulatory layers. These findings provide novel insights into the multilayered genetic architecture controlling meat quality traits in beef cattle, supporting the use of integrative omics to guide functional genomic selection
Multi-User Laboratory of Functional Genomics Applied to Agriculture and Agroenergy, ESALQ - University of Sao Paulo