Applying multi-omics data to study the genetic background of bovine respiratory disease infection in feedlot crossbred cattle.

Abstract

Bovine respiratory disease (BRD) is the most common and costly infectious disease affecting the wellbeing and productivity of beef cattle in North America. BRD is a complex disease whose development is dependent on environmental factors and host genetics. Due to the polymicrobial nature of BRD, our understanding of the genetic and molecular mechanisms underlying the disease is still limited. This knowledge would augment the development of better genetic/genomic selection strategies and more accurate diagnostic tools to reduce BRD prevalence. Therefore, this study aimed to utilize multi-omics data (genomics, transcriptomics, and metabolomics) analyses to study the genetic and molecular mechanisms of BRD infection. Blood samples of 143 cattle (80 BRD; 63 non-BRD animals) were collected for genotyping, RNA sequencing, and metabolite profiling. Firstly, a genome-wide association study (GWAS) was performed for BRD susceptibility using 207,038 SNPs. Two SNPs (Chr5:25858264 and BovineHD1800016801) were identified as associated (p-value <1 × 10-5) with BRD susceptibility. Secondly, differential gene expression between BRD and non-BRD animals was studied. At the significance threshold used (log2FC>2, logCPM>2, and FDR<0.01), 101 differentially expressed (DE) genes were identified. These DE genes significantly (p-value <0.05) enriched several immune responses related functions such as inflammatory response. Additionally, we performed expression quantitative trait loci (eQTL) analysis and identified 420 cis-eQTLs and 144 trans-eQTLs significantly (FDR <0.05) associated with the expression of DE genes. Interestingly, eQTL results indicated the most significant SNP (Chr5:25858264) identified via GWAS was a cis-eQTL for DE gene GPR84. This analysis also demonstrated that an important SNP (rs209419196) located in the promoter region of the DE gene BPI significantly influenced the expression of this gene. Finally, the abundance of 31 metabolites was significantly (FDR <0.05) different between BRD and non-BRD animals, and 17 of them showed correlations with multiple DE genes, which shed light on the interactions between immune response and metabolism. This study identified associations between genome, transcriptome, metabolome, and BRD phenotype of feedlot crossbred cattle. The findings may be useful for the development of genomic selection strategies for BRD susceptibility, and for the development of new diagnostic and therapeutic tools.