Genome-wide association study of disease resilience traits from a natural polymicrobial disease challenge model in pigs identifies the importance of the major histocompatibility complex region

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, functional pathways, and differentially expressed genes subject to physiological states. Multiple quantitative trait loci were detected for all recorded performance and clinical disease traits. The major histocompatibility complex 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 4 quantitative trait loci in the major histocompatibility complex region for growth rate in the late nursery that spanned the subregions for class I, II, and III, with 1 single-nucleotide polymorphism in the major histocompatibility complex class I subregion capturing the largest effects, explaining 0.8–27.1% of genetic variance for growth rate and for multiple clinical disease traits. This single-nucleotide polymorphism was located in the enhancer of TRIM39 gene, which is involved in innate immune response. The major histocompatibility complex 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 major histocompatibility complex 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 quantitative trait loci, 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 major histocompatibility complex and other quantitative trait loci that harbor immune-related genes were identified to be associated with disease resilience traits in a large-scale natural polymicrobial disease challenge. The major histocompatibility complex region was pleiotropic for growth rate under challenge and for clinical disease traits. Four quantitative trait loci were identified across the class I, II, and III subregions of the major histocompatibility complex for nursery growth rate under challenge, with 1 single-nucleotide polymorphism in the major histocompatibility complex class I subregion capturing the largest effects. The major histocompatibility complex and other quantitative trait loci 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 single-nucleotide polymorphism in the major histocompatibility complex class I subregion.

A Comparison of the Behavior, Physiology, and Offspring Resilience of Gestating Sows When Raised in a Group Housing System and Individual Stalls

Simple Summary

The housing patterns of gestating sows affect their health and welfare. In this study, the differences between behavior and stress hormone levels were assessed when sows were housed in a group housing system compared to individual stalls; in addition, the disease resistance and resilience of their piglets were compared. In our investigation, the group-housed sows showed more exploratory behavior, less vacuum chewing, less sitting behavior, and lower stress hormone levels throughout pregnancy. A lipopolysaccharide (LPS) injection test revealed that the offspring of group-housed sows showed better resistance and resilience to disease. Therefore, the gestating sows raised in a group housing system and their piglets are healthier and have improved welfare. Our results show that a group housing system provides higher welfare standards, with conditions that are more suitable for gestating sows in modern pig production.

Abstract

Being in a confined environment causes chronic stress in gestating sows, which is detrimental for sow health, welfare and, consequently, offspring physiology. This study assessed the health and welfare of gestating sows housed in a group housing system compared to individual gestation stalls. After pregnancy was confirmed, experimental sows were divided randomly into two groups: the group housing system (GS), with the electronic sow feeding (ESF) system; or individual stall (IS). The behavior of sows housed in the GS or IS was then compared; throughout pregnancy, GS sows displayed more exploratory behavior, less vacuum chewing, and less sitting behavior (p < 0.05). IS sows showed higher stress hormone levels than GS sows. In particular, at 41 days of gestation, the concentration of the adrenocorticotropic hormone (ACTH) and adrenaline (A) in IS sows was significantly higher than that of GS sows, and the A level of IS sows remained significantly higher at 71 days of gestation (p < 0.01). The lipopolysaccharide (LPS) test was carried out in the weaned piglets of the studied sows. Compared with the offspring of gestating sows housed in GS (PG) or IS (PS), PG experienced a shorter period of high temperature and showed a quicker return to the normal state (p < 0.05). Additionally, their lower levels of stress hormone (p < 0.01) suggest that PG did not suffer from as much stress as PS. These findings suggested that gestating sows housed in GS were more able to carry out their natural behaviors and, therefore, had lower levels of stress and improved welfare. In addition, PG also showed better disease resistance and resilience. These results will provide a research basis for the welfare and breeding of gestating sows.

Correlated Response to Selection for Litter Size Residual Variability in Rabbits’ Body Condition

A divergent selection experiment for residual variance of litter size at birth was carried out in rabbits during twelve generations. Residual variance of litter size was estimated as the within-doe variance of litter size after pre-correction for year and season as well as parity and lactation status effects. The aim of this work was to study the correlated response to selection for litter size residual variability in body condition from mating to weaning. Body condition is related directly to an animal’s fat deposits. Perirenal fat is the main fat deposit in rabbits. Individual body weight (IBW) and perirenal fat thickness (PFT) were used to measure body condition at second mating, delivery, 10 days after delivery, and weaning. Litter size of the first three parities was analyzed. Both lines decreased body condition between mating to delivery; however, the decrease in body condition at delivery was lower in the low line, despite this line having higher litter size at birth (+0.54 kits, p = 0.93). The increment of body condition between delivery and early lactation was slightly higher in the low line. On the other hand, body condition affected success of females’ receptivity and fertility at the third mating, e.g., receptive females showed a higher IBW and PFT than unreceptive ones (+129 g and +0.28 mm, respectively), and fertile females had a higher IBW and PFT than unfertile ones (+82 g and +0.28 mm, respectively). In conclusion, the does selected for reducing litter size variability showed a better deal with situations of high-energy demand, such as delivery and lactation, than those selected for increasing litter size variability, which would agree with the better health and welfare condition in the low line.

Selection for Favorable Health Traits: A Potential Approach to Cope with Diseases in Farm Animals

Disease is a global problem for animal farming industries causing tremendous economic losses (>USD 220 billion over the last decade) and serious animal welfare issues. The limitations and deficiencies of current non-selection disease control methods (e.g., vaccination, treatment, eradication strategy, genome editing, and probiotics) make it difficult to effectively, economically, and permanently eliminate the adverse influences of disease in the farm animals. These limitations and deficiencies drive animal breeders to be more concerned and committed to dealing with health problems in farm animals by selecting animals with favorable health traits. Both genetic selection and genomic selection contribute to improving the health of farm animals by selecting certain health traits (e.g., disease tolerance, disease resistance, and immune response), although both of them face some challenges. The objective of this review was to comprehensively review the potential of selecting health traits in coping with issues caused by diseases in farm animals. Within this review, we highlighted that selecting health traits can be applied as a method of disease control to help animal agriculture industries to cope with the adverse influences caused by diseases in farm animals. Certainly, the genetic/genomic selection solution cannot solve all the disease problems in farm animals. Therefore, management, vaccination, culling, medical treatment, and other measures must accompany selection solution to reduce the adverse impact of farm animal diseases on profitability and animal welfare.

Opportunities to Improve Resilience in Animal Breeding Programs

Resilience is the capacity of an animal to be minimally affected by disturbances or to rapidly return to the state pertained before exposure to a disturbance. However, indicators for general resilience to environmental disturbances have not yet been defined, and perhaps therefore resilience is not yet included in breeding goals. The current developments on big data collection give opportunities to determine new resilience indicators based on longitudinal data, which can aid to incorporate resilience in animal breeding goals. The objectives of this paper were: (1) to define resilience indicator traits based on big data, (2) to define economic values for resilience, and (3) to show the potential to improve resilience of livestock through inclusion of resilience in breeding goals. Resilience might be measured based on deviations from expected production levels over a period of time. Suitable resilience indicators could be the variance of deviations, the autocorrelation of deviations, the skewness of deviations, and the slope of a reaction norm. These (new) resilience indicators provide opportunity to include resilience in breeding programs. Economic values of resilience indicators in the selection index can be calculated based on reduced costs due to labor and treatments. For example, when labor time is restricted, the economic value of resilience increases with an increasing number of animals per farm, and can become as large as the economic value of production. This shows the importance of including resilience in breeding goals. Two scenarios were described to show the additional benefit of including resilience in breeding programs. These examples showed that it is hard to improve resilience with only production traits in the selection index, but that it is possible to greatly improve resilience by including resilience indicators in the selection index. However, when health-related traits are already present in the selection index, the effect is smaller. Nevertheless, inclusion of resilience indicators in the selection index increases the response in the breeding goal and resilience, which results in less labor-demanding, and thus easier-to-manage livestock. Current developments on massive collection of data, and new phenotypes based on these data, offer exciting opportunities to breed for improved resilience of livestock.

Novel Resilience Phenotypes Using Feed Intake Data From a Natural Disease Challenge Model in Wean-to-Finish Pigs

The objective of this study was to extract novel phenotypes related to disease resilience using daily feed intake data from growing pigs under a multifactorial natural disease challenge that was designed to mimic a commercial environment with high disease pressure to maximize expression of resilience. Data used were the first 1,341 crossbred wean-to-finish pigs from a research facility in Québec, Canada. The natural challenge was established under careful veterinary oversight by seeding the facility with diseased pigs from local health-challenged farms, targeting various viral and bacterial diseases, and maintaining disease pressure by entering batches of 60–75 pigs in a continuous flow system. Feed intake (FI) is sensitive to disease, as pigs tend to eat less when they become ill. Four phenotypes were extracted from the individual daily FI data during finishing as novel measures of resilience. The first two were daily variability in FI or FI duration, quantified by the root mean square error (RMSE) from the within individual regressions of FI or duration at the feeder (DUR) on age (RMSE_FI and RMSE_DUR). The other two were the proportion of off-feed days, classified based on negative residuals from a 5% quantile regression (QR) of daily feed intake or duration data on age across all pigs (QR_FI and QR_DUR). Mortality and treatment rate had a heritability of 0.13 (±0.05) and 0.29 (±0.07), respectively. Heritability estimates for RMSE_FI, RMSE_DUR, QR_FI, and QR_DUR were 0.21 (±0.07) 0.26 (±0.07), 0.15 (±0.06), and 0.23 (±0.07), respectively. Genetic correlations of RMSE and QR measures with mortality and treatment rate ranged from 0.37 to 0.85, with QR measures having stronger correlations with both. Estimates of genetic correlations of RMSE measures with production traits were typically low, but often favorable (e.g., −0.31 between RMSE_FI and finishing ADG). Although disease resilience was our target, fluctuations in FI and duration can be caused by many factors other than disease and should be viewed as overall indicators of general resilience to a variety of stressors. In conclusion, daily variation in FI or duration at the feeder can be used as heritable measures of resilience.