Genomic analysis of bovine respiratory disease resistance in preweaned dairy calves diagnosed by a combination of clinical signs and thoracic ultrasonography - Maria G. Strillacci; Vincenzo Ferrulli; Francesca Bernini; Davide Pravettoni; Alessandro Bagnato; Ilaria Martucci; Antonio Boccardo (PLoS ONE, 2025)
Bovine respiratory disease (BRD) poses a significant risk of morbidity and mortality in preweaned dairy calves. Research indicates that this multifactorial disorder can be attributed to the involvement of various pathogens. Currently, there is little information from genome-wide association studies (GWAS) for BRD resistance in young calves based on objective measures and classification of the disease. In this study, we moved forward in phenotyping BRD by coupling two diagnostic tests, the thoracic ultrasonography (TUS) and Wisconsin respiratory score (WISC), in order to assess susceptible and resistant animals to BRD. A total of 240 individuals were scored for BRD using TUS and WISC. A GWAS was performed using a selective genotyping approach to identify Quantitative Trait Loci (QTL) for BRD resistance. A total of 47 calves classified as BRD resistant (TUS ≤  1/ WISC ≤  4) and 47 as BRD susceptible (TUS =  5/ any WISC) were genotyped with the NEOGEN’s GGP Bovine 100K SNP chip. QTL were then identified comparing the SNPs allelic frequencies between the two groups. A total of 28 QTL regions (QTLRs) were defined according to significative SNPs, 141 genes were annotated in the defined QTLRs. The genes were functionally classified into 4 main categories, i.e., i) regulation of systemic arterial blood pressure, ii) fertility, iii) immune function, and iv) filament cytoskeleton. Furthermore, 61 out of 141 genes identified here can be considered promising candidate genes since they were already associated with BRD resistance in published GWAS studies in dairy cattle. The ASB9, BMX, EPSTI1, and OLFM4 genes were identified in 4 of the 6 considered studies. This study paves the way for further research to mine the genome for resistance to respiratory diseases, utilizing an accurate classification process.