Gene set enrichment analysis of <scp>SNP</scp> data in dairy and beef cattle with bovine respiratory disease

Abstract

Bovine respiratory disease (BRD) is a complex disease that is associated with infection by bacterial and viral pathogens when cattle fail to adequately respond to stress. The objective of this study was to use gene set enrichment analysis of SNP data (GSEA-SNP) and a network analysis (ingenuity pathway analysis) to identify gene sets, genes within gene sets (leading-edge genes) and upstream regulators associated with BRD in pre-weaned dairy calves and beef feedlot cattle. BRD cases and controls were diagnosed using the McGuirk health scoring system. Holstein calves were sampled from commercial calf-raising facilities in California (1003 cases and 1011 controls) and New Mexico (376 cases and 372 controls). Commercial feedlot cattle were sampled from Colorado (500 cases and 499 controls) and Washington (504 cases and 497 controls). There were 102 and 237 unique leading-edge genes identified in the dairy calf and beef cattle populations respectively. Six leading-edge genes (ADIPOQ, HTR2A, MIF, PDE6G, PRDX3 and SNCA) were associated with BRD in both dairy and beef cattle. Network analysis identified glucose as the most influential upstream regulator in dairy cattle, whereas in beef cattle, TNF was the most influential upstream regulator. The genes, gene sets and upstream regulators associated with BRD have common functions associated with immunity, inflammation and pulmonary disease and provide insights into the mechanisms that are critical to BRD susceptibility in cattle.