Abstract
Infectious diseases cause tremendous financial losses in the pork industry, emphasizing the importance of disease resilience, which is the ability of an animal to maintain performance under disease. Previously, a natural polymicrobial disease challenge model was established, in which pigs were challenged in the late nursery phase by multiple pathogens to maximize expression of genetic differences in disease resilience. Genetic analysis found that performance traits in this model, including growth rate, feed and water intake, and carcass traits, as well as clinical disease phenotypes, were heritable and could be selected for to increase disease resilience of pigs. The objectives of the current study were to identify genomic regions that are associated with disease resilience in this model, using genome-wide association studies and fine mapping methods, and to use gene set enrichment analyses to determine whether genomic regions associated with disease resilience are enriched for previously published quantitative trait loci (QTL), functional pathways, and differentially expressed genes subject to physiological states. Multiple QTL were detected for all recorded performance and clinical disease traits. The major histocompatibility complex (MHC) region was found to explain substantial genetic variance for multiple traits, including for growth rate in the late nursery (12.8%) and finisher (2.7%), for several clinical disease traits (up to 2.7%), and for several feeding and drinking traits (up to 4%). Further fine mapping identified four QTL in the MHC region for growth rate in the late nursery that spanned the subregions for class I, II, and III, with one SNP in the MHC Class I subregion capturing the largest effects, explaining 0.8 to 27.1% of genetic variance for growth rate and for multiple clinical disease traits. This SNP was located in the enhancer of TRIM39 gene, which is involved in innate immune response. The MHC region was pleiotropic for growth rate in the late nursery and finisher, and for treatment and mortality rates. Growth rate in the late nursery showed strong negative genetic correlations in the MHC region with treatment or mortality rates (-0.62 to -0.85) and a strong positive genetic correlation with growth rate in the finisher (0.79). Gene set enrichment analyses found genomic regions associated with resilience phenotypes to be enriched for previously identified disease susceptibility and immune capacity QTL, for genes that were differentially expressed following bacterial or virus infection and immune response, and for gene ontology terms related to immune and inflammatory response. In conclusion, the MHC and other QTL that harbor immune related genes were identified to be associated with disease resilience traits in a large-scale natural polymicrobial disease challenge. The MHC region was pleiotropic for growth rate under challenge and for clinical disease traits. Four QTL were identified across the class I, II, and III subregions of the MHC for nursery growth rate under challenge, with one SNP in the MHC Class I subregion capturing the largest effects. The MHC and other QTL identified play an important role in host response to infectious diseases and can be incorporated in selection to improve disease resilience, in particular the identified SNP in the MHC Class I subregion.