Exploring Phenotypes for Disease Resilience in Pigs Using Complete Blood Count Data From a Natural Disease Challenge Model

Inheritance of feed intake-based resilience traits and their correlation with production traits in Finnish pig breeds

High resilience against diseases, changing environmental conditions, and other stress factors and the ability to efficiently recover to normal status, is becoming increasingly important in pig production. Finding new phenotypes that relate to resilience is a crucial step for improving the resilience of pigs through selection. The objective of this study was to extract resilience-related phenotypes based on fluctuations in daily feed intake (DFI, g) and time spent in feeding per day (TPD, min) and to estimate the heritability of these traits and genetic correlations with production traits (PT). Resilience-related traits with high enough heritability and with either favorable or neutral genetic correlation with PT could be used in the selection program to improve the productivity and welfare of pigs. In this study, we used data from 7,347 Finnish Yorkshire, Landrace, and crossbred pigs raised at the test station. Six pig-specific resilience-related phenotypes were extracted from the individual DFI and TPD: root mean square error (RMSE), quantile regression (QR), and coefficient of variation (CV). RMSE was calculated from the differences between the actual DFI (or TPD) and the pig-specific predicted values. QR was based on the number of days that a pig belonged to the group with the lowest 5% of pigs based on DFI (or TPD), and CV was calculated over the daily observations of DFI (or TPD). PT included average daily gain (ADG, g), backfat thickness (BF, mm), and feed conversion rate (FCR, g/g). The heritability estimates for resilience-related traits varied between 0.07 ± 0.02 (QRDFI) and 0.20 ± 0.03 (RMSETPD). The genetic correlations between resilience-related traits and PT were mostly neutral, but for example, RMSEDFI had a favorable genetic correlation with FCR and BF but an unfavorable correlation with ADG. Lastly, we observed that pigs belonging to the lowest 10% group based on their breeding value (BV) for QRTPD had a lower proportion (10% incidence) of sick days compared to the highest 10% BV group (30% incidence). Therefore, pigs exhibiting small TPD variation (related to high resilience) tend to be less susceptible to sickness than pigs with large TPD variation (related to low resilience). Given its moderate heritability, neutral genetic correlation with PT, and positive effect on health, QRTPD can be considered the most promising resilience-related trait in the Finnish production system.

Identification of intestinal and fecal microbial biomarkers using a porcine social stress model

Understanding the relationships between social stress and the gastrointestinal microbiota, and how they influence host health and performance is expected to have many scientific and commercial implementations in different species, including identification and improvement of challenges to animal welfare and health. In particular, the study of the stress impact on the gastrointestinal microbiota of pigs may be of interest as a model for human health. A porcine stress model based on repeated regrouping and reduced space allowance during the last 4 weeks of the finishing period was developed to identify stress-induced changes in the gut microbiome composition. The application of the porcine stress model resulted in a significant increase in salivary cortisol concentration over the course of the trial and decreased growth performance and appetite. The applied social stress resulted in 32 bacteria being either enriched (13) or depleted (19) in the intestine and feces. Fecal samples showed a greater number of microbial genera influenced by stress than caecum or colon samples. Our trial revealed that the opportunistic pathogens Treponema and Clostridium were enriched in colonic and fecal samples from stressed pigs. Additionally, genera such as Streptococcus, Parabacteroides, Desulfovibrio, Terrisporobacter, Marvinbryantia, and Romboutsia were found to be enriched in response to social stress. In contrast, the genera Prevotella, Faecalibacterium, Butyricicoccus, Dialister, Alloprevotella, Megasphaera, and Mitsuokella were depleted. These depleted bacteria are of great interest because they synthesize metabolites [e.g., short-chain fatty acids (SCFA), in particular, butyrate] showing beneficial health benefits due to inhibitory effects on pathogenic bacteria in different animal species. Of particular interest are Dialister and Faecalibacterium, as their depletion was identified in a human study to be associated with inferior quality of life and depression. We also revealed that some pigs were more susceptible to pathogens as indicated by large enrichments of opportunistic pathogens of Clostridium, Treponema, Streptococcus and Campylobacter. Generally, our results provide further evidence for the microbiota-gut-brain axis as indicated by an increase in cortisol concentration due to social stress regulated by the hypothalamic-pituitary-adrenal axis, and a change in microbiota composition, particularly of bacteria known to be associated with pathogenicity and mental health diseases.

GWAS and genetic and phenotypic correlations of plasma metabolites with complete blood count traits in healthy young pigs reveal implications for pig immune response

Introduction: In this study estimated genetic and phenotypic correlations between fifteen complete blood count (CBC) traits and thirty-three heritable plasma metabolites in young healthy nursery pigs. In addition, it provided an opportunity to identify candidate genes associated with variation in metabolite concentration and their potential association with immune response, disease resilience, and production traits.

Methods: The blood samples were collected from healthy young pigs and Nuclear Magnetic Resonance (NMR) was used to quantify plasma metabolites. CBC was determined using the ADVIA® 2120i Hematology System. Genetic correlations of metabolite with CBC traits and single step genome-wide association study (ssGWAS) were estimated using the BLUPF90 programs.

Results: Results showed low phenotypic correlation estimates between plasma metabolites and CBC traits. The highest phenotypic correlation was observed between lactic acid and plasma basophil concentration (0.36 ± 0.04; p < 0.05). Several significant genetic correlations were found between metabolites and CBC traits. The plasma concentration of proline was genetically positively correlated with hemoglobin concentration (0.94 ± 0.03; p < 0.05) and L-tyrosine was negatively correlated with mean corpuscular hemoglobin (MCH; −0.92 ± 0.74; p < 0.05). The genomic regions identified in this study only explained a small percentage of the genetic variance of metabolites levels that were genetically correlated with CBC, resilience, and production traits.

Discussion: The results of this systems approach suggest that several plasma metabolite phenotypes are phenotypically and genetically correlated with CBC traits, suggesting that they may be potential genetic indicators of immune response following disease challenge. Genomic analysis revealed genes and pathways that might interact to modulate CBC, resilience, and production traits.

Exploration of plasma metabolite levels in healthy nursery pigs in response to environmental enrichment and disease resilience

The purpose of this study was to explore plasma metabolite levels in young healthy pigs and their potential association with disease resilience and estimate genetic and phenotypic correlation with the change in lymphocyte concentration following disease challenge. Plasma samples were collected from 968 healthy nursery pigs over 15 batches at an average of 28 ± 3.23 d of age. Forty-four metabolites were identified and quantified by nuclear magnetic resonance. Pigs were then introduced into a natural disease challenge barn, and were classified into four groups based on the growth rate of each animal in the grow-to-finish phase (GFGR) and treatment rate (TR): resilient (RES), average (MID), susceptible (SUS), and dead (pigs that died before harvest). Blood samples were collected from all pigs before and 2 wk after disease challenge and complete blood count was determined. Environmental enrichment (inedible point source objects) was provided for half of the pigs in seven batches (N = 205) to evaluate its impact on resilience and metabolite concentrations. Concentration of all metabolites was affected by batch, while entry age affected the concentration of 16 metabolites. The concentration of creatinine was significantly lower for pigs classified as "dead" and "susceptible" when compared to "average" (P < 0.05). Pigs that received enrichment had significantly lower concentrations of six metabolites compared with pigs that did not receive enrichment (P ≤ 0.05). Both, group classification and enrichment affected metabolites that are involved in the same pathways of valine, leucine, and isoleucine biosynthesis and degradation. Resilient pigs had higher increase in lymphocyte concentration after disease challenge. The concentration of plasma l-α-aminobutyric acid was significantly negatively genetically correlated with the change in lymphocyte concentration following challenge. In conclusion, creatinine concentration in healthy nursery pigs was lower in pigs classified as susceptible or dead after disease challenge, whilst l-α-aminobutyric may be a genetic biomarker of lymphocyte response after pathogen exposure, and both deserve further investigation. Batch, entry age, and environmental enrichment were important factors affecting the concentration of metabolites and should be taken into consideration in future studies.

Breeding for disease resilience: opportunities to manage polymicrobial challenge and improve commercial performance in the pig industry

Disease resilience, defined as an animal's ability to maintain productive performance in the face of infection, provides opportunities to manage the polymicrobial challenge common in pig production. Disease resilience can deliver a number of benefits, including more sustainable production as well as improved animal health and the potential for reduced antimicrobial use. However, little progress has been made to date in the application of disease resilience in breeding programs due to a number of factors, including (1) confusion around definitions of disease resilience and its component traits disease resistance and tolerance, and (2) the difficulty in characterizing such a complex trait consisting of multiple biological functions and dynamic elements of rates of response and recovery from infection. Accordingly, this review refines the definitions of disease resistance, tolerance, and resilience based on previous studies to help improve the understanding and application of these breeding goals and traits under different scenarios. We also describe and summarize results from a "natural disease challenge model" designed to provide inputs for selection of disease resilience. The next steps for managing polymicrobial challenges faced by the pig industry will include the development of large-scale multi-omics data, new phenotyping technologies, and mathematical and statistical methods adapted to these data. Genome editing to produce pigs resistant to major diseases may complement selection for disease resilience along with continued efforts in the more traditional areas of biosecurity, vaccination and treatment. Altogether genomic approaches provide exciting opportunities for the pig industry to overcome the challenges provided by hard-to-manage diseases as well as new environmental challenges associated with climate change.

Heritability and genetic correlations of plasma metabolites of pigs with production, resilience and carcass traits under natural polymicrobial disease challenge

Metabolites in plasma of healthy nursery pigs were quantified using nuclear magnetic resonance. Heritabilities of metabolite concentration were estimated along with their phenotypic and genetic correlations with performance, resilience, and carcass traits in growing pigs exposed to a natural polymicrobial disease challenge. Variance components were estimated by GBLUP. Heritability estimates were low to moderate (0.11 ± 0.08 to 0.19 ± 0.08) for 14 metabolites, moderate to high (0.22 ± 0.09 to 0.39 ± 0.08) for 17 metabolites, and highest for l-glutamic acid (0.41 ± 0.09) and hypoxanthine (0.42 ± 0.08). Phenotypic correlation estimates of plasma metabolites with performance and carcass traits were generally very low. Significant genetic correlation estimates with performance and carcass traits were found for several measures of growth and feed intake. Interestingly the plasma concentration of oxoglutarate was genetically negatively correlated with treatments received across the challenge nursery and finisher (− 0.49 ± 0.28; P < 0.05) and creatinine was positively correlated with mortality in the challenge nursery (0.85 ± 0.76; P < 0.05). These results suggest that some plasma metabolite phenotypes collected from healthy nursery pigs are moderately heritable and genetic correlations with measures of performance and resilience after disease challenge suggest they may be potential genetic indicators of disease resilience.

A Methodology to Quantify Resilience in Growing Pigs

Simple Summary

The concept of resilience can be defined as the ability of animals to maintain their productivity despite the stressors that might occur during the rearing period. Despite the growing interest in the genetic determinism of resilience and its possible inclusion in selection objectives, there is no straightforward method to measure this trait. Several quantifying methods estimate resilience based on productivity such as body weight or milk production, or non-productivity related traits such as immunity or stress responses. The objective of this study was to elaborate novel resilience indicators in growing pigs based on both productivity (body weight) and non-productivity (acute-phase proteins) related traits. We propose the deviation from the expected growth curve and the increment of the acute-phase protein haptoglobin, after applying a common vaccine, as resilience indicators in growing pigs under standard rearing conditions. We showed that the suggested resilience indicators are under a genetic control, show a substantial variability in the population, and may be improved through selection.

Abstract

There is a growing concern about the genetic determinism of resilience and its possible implementation in breeding programs. The objective of our study was to elaborate novel resilience indicators in growing pigs based on the deviation from the expected growth curve and the increment of the acute-phase protein haptoglobin (HP) after applying a common vaccine. A total of 445 pigs were vaccinated with an attenuated Aujeszky vaccine at 12 weeks of age. Deviation from the expected body weight (ΔBW) given the growth curve of unvaccinated pigs at 28 days post-vaccination (DPV) and the increment of HP at 4 DPV (ΔHP) were suggested as resilience indicators. Challenged pigs that maintained their productivity and had a minor activation of HP were deemed resilient, whereas pigs that had low ∆BW values and a high activation of HP were deemed susceptible. Pigs were also classified based on ∆BW and ∆HP relative to the expected BW at 28 DPV and to the basal level of HP, respectively. The concordance was high between both methods, indicating that ΔBW and ΔHP are not sensitive to the animal’s expected BW nor the basal level of HP. The heritability estimates were moderate for ∆BW (0.33) and low-to-moderate for ∆HP (0.16). Our study suggests ΔBW and ΔHP as novel resilience indicators in pigs. The suggested indicators capture different aspects of resilience, are easy to measure, and are genetically controlled. Thus, they may be improved through selective breeding. Further analyses are needed to validate our findings.

Quantitative analysis of the blood transcriptome of young healthy pigs and its relationship with subsequent disease resilience

Background

Disease resilience, which is the ability of an animal to maintain performance under disease, is important for pigs in commercial herds, where they are exposed to various pathogens. Our objective was to investigate population-level gene expression profiles in the blood of 912 healthy F1 barrows at ~ 27 days of age for associations with performance and health before and after their exposure to a natural polymicrobial disease challenge at ~ 43 days of age.

Results

Most significant (q < 0.20) associations of the level of expression of individual genes in blood of young healthy pigs were identified for concurrent growth rate and subjective health scores prior to the challenge, and for mortality, a combined mortality-treatment trait, and feed conversion rate after the challenge. Gene set enrichment analyses revealed three groups of gene ontology biological process terms that were related to disease resilience: 1) immune and stress response-related terms were enriched among genes whose increased expression was unfavorably associated with both pre- and post-challenge traits, 2) heme-related terms were enriched among genes that had favorable associations with both pre- and post-challenge traits, and 3) terms related to protein localization and viral gene expression were enriched among genes that were associated with reduced performance and health traits after but not before the challenge.

Conclusions

Gene expression profiles in blood from young healthy piglets provide insight into their performance when exposed to disease and other stressors. The expression of genes involved in stress response, heme metabolism, and baseline expression of host genes related to virus propagation were found to be associated with host response to disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07912-8.

Investigating the genetic architecture of disease resilience in pigs by genome-wide association studies of complete blood count traits collected from a natural disease challenge model

Background

Genetic improvement for disease resilience is anticipated to be a practical method to improve efficiency and profitability of the pig industry, as resilient pigs maintain a relatively undepressed level of performance in the face of infection. However, multiple biological functions are known to be involved in disease resilience and this complexity means that the genetic architecture of disease resilience remains largely unknown. Here, we conducted genome-wide association studies (GWAS) of 465,910 autosomal SNPs for complete blood count (CBC) traits that are important in an animal’s disease response. The aim was to identify the genetic control of disease resilience.

Results

Univariate and multivariate single-step GWAS were performed on 15 CBC traits measured from the blood samples of 2743 crossbred (Landrace × Yorkshire) barrows drawn at 2-weeks before, and at 2 and 6-weeks after exposure to a polymicrobial infectious challenge. Overall, at a genome-wise false discovery rate of 0.05, five genomic regions located on Sus scrofa chromosome (SSC) 2, SSC4, SSC9, SSC10, and SSC12, were significantly associated with white blood cell traits in response to the polymicrobial challenge, and nine genomic regions on multiple chromosomes (SSC1, SSC4, SSC5, SSC6, SSC8, SSC9, SSC11, SSC12, SSC17) were significantly associated with red blood cell and platelet traits collected before and after exposure to the challenge. By functional enrichment analyses using Ingenuity Pathway Analysis (IPA) and literature review of previous CBC studies, candidate genes located nearby significant single-nucleotide polymorphisms were found to be involved in immune response, hematopoiesis, red blood cell morphology, and platelet aggregation.

Conclusions

This study helps to improve our understanding of the genetic basis of CBC traits collected before and after exposure to a polymicrobial infectious challenge and provides a step forward to improve disease resilience.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07835-4.

Why breed disease-resilient livestock, and how?

BACKGROUND

Fighting and controlling epidemic and endemic diseases represents a considerable cost to livestock production. Much research is dedicated to breeding disease resilient livestock, but this is not yet a common objective in practical breeding programs. In this paper, we investigate how future breeding programs may benefit from recent research on disease resilience.

MAIN BODY

We define disease resilience in terms of its component traits resistance (R: the ability of a host animal to limit within-host pathogen load (PL)) and tolerance (T: the ability of an infected host to limit the damage caused by a given PL), and model the host's production performance as a reaction norm on PL, depending on R and T. Based on this, we derive equations for the economic values of resilience and its component traits. A case study on porcine respiratory and reproductive syndrome (PRRS) in pigs illustrates that the economic value of increasing production in infectious conditions through selection for R and T can be more than three times higher than by selection for production in disease-free conditions. Although this reaction norm model of resilience is helpful for quantifying its relationship to its component traits, its parameters are difficult and expensive to quantify. We consider the consequences of ignoring R and T in breeding programs that measure resilience as production in infectious conditions with unknown PL-particularly, the risk that the genetic correlation between R and T is unfavourable (antagonistic) and that a trade-off between them neutralizes the resilience improvement. We describe four approaches to avoid such antagonisms: (1) by producing sufficient PL records to estimate this correlation and check for antagonisms-if found, continue routine PL recording, and if not found, shift to cheaper proxies for PL; (2) by selection on quantitative trait loci (QTL) known to influence both R and T in favourable ways; (3) by rapidly modifying towards near-complete resistance or tolerance, (4) by re-defining resilience as the animal's capacity to resist (or recover from) the perturbation caused by an infection, measured as temporal deviations of production traits in within-host longitudinal data series.

CONCLUSIONS

All four alternatives offer promising options for genetic improvement of disease resilience, and most rely on technological and methodological developments and innovation in automated data generation.