Use of nCounter mRNA Profiling to Identify at-arrival Gene Expression Patterns for Predicting Bovine Respiratory Disease in Beef Cattle

Background Transcriptomics has identified at-arrival differentially expressed genes associated with bovine respiratory disease (BRD) development; however, their use as prediction molecules necessitates further evaluation. Therefore, we aimed to selectively analyze and corroborate at-arrival mRNA expression from multiple independent populations of beef cattle. In a nested case-control study, we evaluated the expression of 56 mRNA molecules from at-arrival blood samples of 234 cattle across seven populations via NanoString nCounter gene expression profiling. Analysis of mRNA was performed with nSolver Advanced Analysis software (p<0.05), comparing cattle groups based on the diagnosis of clinical BRD within 28 days of facility arrival (n=115 Healthy; n=119 BRD); BRD was further stratified for severity based on frequency of treatment and/or mortality (Treated_1, n=89; Treated_2+, n=30). Gene expression homogeneity of variance, receiver operator characteristic (ROC) curve, and decision tree analyses were performed between severity cohorts. Results Increased expression of mRNAs involved in specialized pro-resolving mediator synthesis ( ALOX15 , HPGD ), leukocyte differentiation ( LOC100297044 , GCSAML , KLF17 ), and antimicrobial peptide production ( CATHL3 , GZMB , LTF ) were identified in Healthy cattle. BRD cattle possessed increased expression of CFB, and mRNA related to granulocytic processes ( DSG1 , LRG1 , MCF2L ) and type-I interferon activity ( HERC6, IFI6, ISG15, MX1 ). Healthy and Treated_1 cattle were similar in terms of gene expression, while Treated_2+ cattle were the most distinct. ROC cutoffs were used to generate an at-arrival treatment decision tree, which classified 90% of Treated_2+ individuals. Conclusions Increased expression of complement factor B, pro-inflammatory, and type I interferon-associated mRNA hallmark the at-arrival expression patterns of cattle that develop severe clinical BRD. Here, we corroborate at-arrival mRNA markers identified in previous transcriptome studies and generate a prediction model to be evaluated in future studies. Further research is necessary to evaluate these expression patterns in a prospective manner.