Search

Well parameterized epidemiological models including accurate representation of contacts are fundamental to controlling epidemics. However, age-stratified contacts are typically estimated from pre-pandemic/peace-time surveys, even though interventions and public response likely alter contacts. Here, we fit age-stratified models, including re-estimation of relative contact rates between age classes, to public data describing the 2020-2021 COVID-19 outbreak in England. This data includes age-stratified population size, cases, deaths, hospital admissions and results from the Coronavirus Infection Survey (almost 9000 observations in all). Fitting stochastic compartmental models to such detailed data is extremely challenging, especially considering the large number of model parameters being estimated (over 150). An efficient new inference algorithm ABC-MBP combining existing approximate Bayesian computation (ABC) methodology with model-based proposals (MBPs) is applied. Modified contact rates are inferred alongside time-varying reproduction numbers that quantify changes in overall transmission due to pandemic response, and age-stratified proportions of asymptomatic cases, hospitalization rates and deaths. These inferences are robust to a range of assumptions including the values of parameters that cannot be estimated from available data. ABC-MBP is shown to enable reliable joint analysis of complex epidemiological data yielding consistent parametrization of dynamic transmission models that can inform data-driven public health policy and interventions. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'. [ABSTRACT FROM AUTHOR]

Trade‐offs between host resistance to parasites and host growth or reproduction can occur due to allocation of limited available resources between competing demands. To predict potential trade‐offs arising from genetic selection for host resistance, a better understanding of the associated nutritional costs is required. Here, we studied resistance costs by using sheep from lines divergently selected on their resistance to a common blood‐feeding gastro‐intestinal parasite (Haemonchus contortus). First, we assessed the effects of selection for high or low host resistance on condition traits (body weight, back fat, and muscle thickness) and infection traits (parasite fecal egg excretion and loss in blood haematocrit) at various life stages, in particular during the periparturient period when resource allocation to immunity may limit host resistance. Second, we analysed the condition–infection relationship to detect a possible trade‐off, in particular during the periparturient period. We experimentally infected young females in four stages over their first 2 years of life, including twice around parturition (at 1 year and at 2 years of age). Linear mixed‐model analyses revealed a large and consistent between‐line difference in infection traits during growth and outside of the periparturient period, whereas this difference was strongly attenuated during the periparturient period. Despite their different responses to infection, lines had similar body condition traits. Using covariance decomposition, we then found that the phenotypic relationship between infection and condition was dominated by direct infection costs arising from parasite development within the host. Accounting for these within‐individual effects, a cost of resistance on body weight was detected among ewes during their first reproduction. Although this cost and the reproductive constraint on resistance are unlikely to represent a major concern for animal breeding in nutrient‐rich environments, this study provides important new insights regarding the nutritional costs of parasite resistance at different lifestages and how these may affect response to selection. [ABSTRACT FROM AUTHOR]

Post-mixing aggression in pigs is a harmful and costly behaviour which negatively impacts both animal welfare and farm efficiency. There is vast unexplained variation in the amount of acute and chronic aggression that dyadic behaviours do not fully explain. This study hypothesised that certain pen-level network properties may improve prediction of lesion outcomes due to the incorporation of indirect social interactions that are not captured by dyadic traits. Utilising current SNA theory, we investigate whether pen-level network properties affect the number of aggression-related injuries at 24 hours and 3 weeks post-mixing (24hr-PM and 3wk-PM). Furthermore we compare the predictive value of network properties to conventional dyadic traits. A total of 78 pens were video recorded for 24hr post-mixing. Each aggressive interaction that occurred during this time period was used to construct the pen-level networks. The relationships between network properties at 24hr and the pen level injuries at 24hr-PM and 3wk-PM were analysed using mixed models and verified using permutation tests. The results revealed that network properties at 24hr could predict long term aggression (3wk-PM) better than dyadic traits. Specifically, large clique formation in the first 24hr-PM predicted fewer injuries at 3wk-PM and high betweenness centralisation at 24hr-PM predicted increased rates of injury at 3wk-PM. This study demonstrates that network properties present during the first 24hr-PM have predictive value for chronic aggression, and have potential to allow identification and intervention for at risk groups. [ABSTRACT FROM AUTHOR]

Background: Macrophages are essential to innate immunity against many pathogens, but some pathogens also target macrophages as routes to infection. The Porcine Reproductive and Respiratory Syndrome virus (PRRSV) is an RNA virus that infects porcine alveolar macrophages (PAMs) causing devastating impact on global pig production. Identifying the cellular mechanisms that mediate PAM susceptibility to the virus is crucial for developing effective interventions. Previous evidence suggests that the scavenger receptor CD163 is essential for productive infection of PAMs with PRRSV. Here we use an integrative in-vitro-in-silico modelling approach to determine whether and how PAM susceptibility to PRRSV changes over time, to assess the role of CD163 expression on such changes, and to infer other potential causative mechanisms altering cell susceptibility. Results: Our in-vitro experiment showed that PAM susceptibility to PRRSV changed considerably over incubation time. Moreover, an increasing proportion of PAMs apparently lacking CD163 were found susceptible to PRRSV at the later incubation stages, thus conflicting with current understanding that CD163 is essential for productive infection of PAMs with PRRSV. We developed process based dynamic mathematical models and fitted these to the data to assess alternative hypotheses regarding potential underlying mechanisms for the observed susceptibility and biomarker trends. The models informed by our data support the hypothesis that although CD163 may have enhanced cell susceptibility, it was not essential for productive infection in our study. Instead the models promote the existence of a reversible cellular state, such as macrophage polarization, mediated in a density dependent manner by autocrine factors, to be responsible for the observed kinetics in cell susceptibility. Conclusions: Our dynamic model-inference approach provides strong support that PAM susceptibility to the PRRS virus is transient, reversible and can be mediated by compounds produced by the target cells themselves, and that these can render PAMs lacking the CD163 receptor susceptible to PRRSV. The results have implications for the development of therapeutics aiming to boost target cell resistance and prompt future investigation of dynamic changes in macrophage susceptibility to PRRSV and other viruses. [ABSTRACT FROM AUTHOR]

The objectives of this study were to determine nitrogen loss at different stages of growth and during the entire growing period and to investigate the associations between nitrogen excretion and production traits in growing pigs. Data from 315 pigs of an F2 population which originated from crossing Pietrain sires with a commercial dam line were used. Nitrogen retention was derived from protein retention as measured using the deuterium dilution technique during different stages of growth (60 to 90 kg, 90 to 120 kg, and 120 to 140 kg). Pigs were fed ad libitum with 2 pelleted diets containing 17% (60 to 90 kg) and 16.5% (90 to 120 and 120 to 140 kg) CP Average daily nitrogen excretion (ADNE) within each stage of growth was calculated on the basis of the accumulated difference between average daily nitrogen intake (ADNI) and average daily nitrogen retention (ADNR). Least ADNE, nitrogen excretion per BW gain (NEWG) and total nitrogen excretion (TNE) were observed during growth from 60 to 90 kg. In contrast, the greatest ADNE, NEWG, and TNE were found during growth from 120 to 140 kg. Statistical analyses indicated that gender, housing type, the ryanodine receptor 1 (RYRl) gene, and batch influenced nitrogen excretion (P < 0.05), but the degree and direction of influences differed between growth stages. Gender differences showed that gilts excreted less nitrogen than barrows (P < 0.05), which was associated with decreased feed conversion ratio (FCR; feed:gain) and lipid:protein gain ratio. Single-housed pigs showed reduced nitrogen excretion compared with group-housed pigs (P < 0.05). In comparison to other genotypes, pigs carrying genotype AW (homozygous normal) at the RYRl locus had the least nitrogen excretion (P < 0.05) at all stages of growth except from 60 to 90 kg. The residual correlations indicated that NEWG and TNE have large positive correlations with FCR (r = 0.99 and 0.91, respectively) and moderate negative correlations with ADG (r = -0.53 and -0.48, respectively), for the entire growing period. Improvement in FCR, increase in ADG and reduction in lipid:protein gain ratio by 1 phenotypic SD reduced TNE per pig by 709 g, 307 g, and 211 g, respectively, over the entire growing period. The results indicate that nitrogen excretion changes substantially during growth, and it can be reduced most effectively by improvement of feed efficiency and to a lesser extent through the improvement of BW gain or body composition or both. [ABSTRACT FROM AUTHOR]

Previous studies have shown that host genetic heterogeneity in the response to infectious challenge can affect the emergence risk and the severity of diseases transmitted through direct contact between individuals. However, there is substantial uncertainty about the degree and direction of influence owing to different definitions of genetic variation, most of which are not in line with the current understanding of the genetic architecture of disease traits. Also, the relevance of previous results for diseases transmitted through environmental sources is unclear. In this article a compartmental genetic-epidemiological model was developed to quantify the impact of host genetic diversity on epidemiological characteristics of diseases transmitted through a contaminated environment. The model was parameterized for footrot in sheep. Genetic variation was defined through continuous distributions with varying shape and degree of dispersion for different disease traits. The model predicts a strong impact of genetic heterogeneity on the disease risk and its progression and severity, as well as on observable host phenotypes, when dispersion in key epidemiological parameters is high. The impact of host variation depends on the disease trait for which variation occurs and on environmental conditions affecting pathogen survival. In particular, compared to homogeneous populations with the same average susceptibility, disease risk and severity are substantially higher in populations containing a large proportion of highly susceptible individuals, and the differences are strongest when environmental contamination is low. The implications of our results for the recording and analysis of disease data and for predicting response to selection are discussed. [ABSTRACT FROM AUTHOR]

Background: Both host genetic potentials for growth and disease resistance, as well as nutrition are known to affect responses of individuals challenged with micro-parasites, but their interactive effects are difficult to predict from experimental studies alone. Methodology/Principal Findings: Here, a mathematical model is proposed to explore the hypothesis that a host's response to pathogen challenge largely depends on the interaction between a host's genetic capacities for growth or disease resistance and the nutritional environment. As might be expected, the model predicts that if nutritional availability is high, hosts with higher growth capacities will also grow faster under micro-parasitic challenge, and more resistant animals will exhibit a more effective immune response. Growth capacity has little effect on immune response and resistance capacity has little effect on achieved growth. However, the influence of host genetics on phenotypic performance changes drastically if nutrient availability is scarce. In this case achieved growth and immune response depend simultaneously on both capacities for growth and disease resistance. A higher growth capacity (achieved e.g. through genetic selection) would be detrimental for the animal's ability to cope with pathogens and greater resistance may reduce growth in the short-term. Significance: Our model can thus explain contradicting outcomes of genetic selection observed in experimental studies and provides the necessary biological background for understanding the influence of selection and/or changes in the nutritional environment on phenotypic growth and immune response. [ABSTRACT FROM AUTHOR]

ABSTRACT: The response to infection from porcine reproductive and respiratory syndrome virus (PRRSV) for 2 genetically diverse commercial pig lines was investigated. Seventy-two pigs from each line, aged 6 wk, were challenged with PRRSV VR-2385, and 66 littermates served as control. The clinical response to infection was monitored throughout the study and pigs were necropsied at 10 or 21 d postinfection. Previous analyses showed significant line differences in susceptibility to PRRSV infection. This study also revealed significant line differences in growth during infection. Line B, characterized by faster growth rate than line A in the absence of infection, suffered more severe clinical disease and greater reduction in BW growth after infection. Correlations between growth and disease-related traits were generally negative, albeit weak. Correlations were also weak among most clinical and pathological traits. Clinical disease traits such as respiratory scores and rectal temperatures were poor indicators of virus levels, pathological damage, or growth during PRRSV infection. Relationships between traits varied over time, indicating that different disease-related mechanisms may operate at different time scales and, therefore, that the time of assessing host responses may influence the conclusions drawn about biological significance. Three possible mechanisms underlying growth under PRRSV infection were proposed based on evidence from this and previous studies. It was concluded that a comprehensive framework describing the interaction between the biological mechanisms and the genetic influence on these would be desirable for achieving progress in the genetic control of this economically important disease. [ABSTRACT FROM AUTHOR]

Abstract: An in silico mathematical model was used to explore the effect of, and the interaction between, (i) nutrition, (ii) genotype for growth and (iii) genotype for resistance, on the estimates of genetic parameters for resistance and performance in a population of lambs trickle-challenged daily with 3,000 L3s of Teladorsagia circumcincta. A previously published model for nematode infections in sheep was developed to include heritable variation in sheep growth traits, as well as in immunologically controlled traits such as establishment of incoming larvae, mortality of the adult worms and fecundity of the adult female worms. The simulated population comprised 10,000 lambs, these being the offspring of 250 sires mated to 5,000 dams. The model assumed the lambs to be parasitologically naïve at weaning (2months of age), at which point the trickle challenge commenced and the model was updated daily until slaughter (at 6months of age). Dietary treatments included a good and a poor quality feed, offered ad libitum. Two genotypes for growth were assumed: (i) fast and (ii) slow growing. Three genotypes for resistance were used: (i) benchmark, (ii) susceptible and (iii) resistant, differing in their ability to cope with nematode infections. Genetic parameters for output traits, including growth rate, food intake, worm burden and faecal egg count were estimated using a linear mixed model, fitting sire as a random effect to capture genetic effects. Heritabilities and correlations were found to change over time. In general, the heritabilities of immunity traits increased over time, whereas genetic correlations between production and immunity traits became weaker. Diet had a significant effect on the means and the estimated correlations of output traits, while genotypes for growth and resistance had smaller effects. These results suggest that discrepancies between published genetic parameters for nematode resistance may be a function of environmental factors rather than differences in host genotype. [Copyright &y& Elsevier]

Abstract: The performance of a visual image analysis (VIA) system was tested with regards to its potential to determine in vivo carcass composition and conformation, either alone, or in conjunction with other in vivo measures such as live weight and backfat depth. Pigs of both sexes of a commercial type were reared and slaughtered at weights ranging from 50 to 120 kg. Feeding was ad libitum on diets ranging from 0.14 to 0.19 kgkg−1 crude protein content to produce animals of a range of body condition. Two analyses were carried out: the first analysis addressed the relationship between dimensionless carcass and VIA indices; the second analysis assessed the relationship between carcass composition and VIA body shape using detrended carcass and VIA data, which were produced by removal of allometric growth trends. A statistically significant relationship (P &#60;0.05) between in vivo VIA body size and shape and carcass muscle dimensions and composition was found for most body regions. Adjusted R 2 statistics ranged between 0.13 and 0.54 for relative fat weights and between 0.14 and 0.51 for relative lean weights. The predictive power of the regression models, indicated by R 2-like statistics for prediction, was approximately 70% of the adjusted R 2 values. The descriptive and predictive powers of the corresponding models generally strengthened if VIA indices were combined with other in vivo measurements. The relationships between in vivo and carcass measures remained statistically significant (P &#60;0.05) after removal of the growth trends, although adjusted R 2 statistics generally decreased. The predictive power of models corresponding to the detrended measures was, however, weak. The results show in vivo VIA measurements to be useful in the estimation of muscle size, carcass conformation and composition, all of which are of significant importance to the pig production, marketing and processing industries. [Copyright &y& Elsevier]

The interest in recirculating aquaculture systems (RAS) is growing due to their benefits such as increased productivity, better control over animal care, reduced environmental effects, and less water consumption. However, in some regions of the world, traditional aquaculture methods remain prevalent, and selective breeding has often been designed for performance within these systems. Therefore, it is important to evaluate how current fish populations fare in RAS to guide future breeding choices. In a commercial setting, we explore the genetic structure of growth characteristics, measure genotype–environment interactions (GxE) in salmon smolts, and examine genetic markers related to growth in freshwater lochs and RAS. Young salmon were raised together until they reached the parr stage, after which they were divided equally between freshwater net‐pens and RAS. After an 8‐week period, we sampled fish from each environment and genotyped them. Our findings revealed that fish reared in RAS were generally smaller in weight and length but exhibited a higher condition factor and uniformity. We found a notably smaller component of unexplained variance in the RAS, leading to higher heritability estimates. We observed a low GxE effect for length and condition factor, but significant re‐ranking for whole‐body weight, as well as noticeable differences in trait associations across environments. Specifically, a segment of chromosome 22 was found to be linked with the condition factor in the RAS population only. Results suggests that if the use of RAS continues to expand, the efficiency of existing commercial populations may not reach its full potential unless breeding programs specific to RAS are implemented. [ABSTRACT FROM AUTHOR]

To develop a critical appraisal tool for non-computational-specialist public health professionals to assess the quality and relevance of modelling studies about Test and Trace (and Protect – TTP) programmes' impact on COVID-19 transmission. Decision-making tool development. Using Tugwell et al.'s 1985 Health Care Effectiveness equation as a conceptual framework, combined with a purposive search of the relevant early modeling literature, we developed six critical appraisal questions for the rapid assessment of modeling studies related to the evaluation of TTP programmes' effectiveness. By applying the critical appraisal tool to selected recent COVID-19 modeling studies, we demonstrate how models can be evaluated using the six questions to evaluate internal and external validity and relevance. These six critical appraisal questions are able to discriminate between modeling studies of higher and lower quality and relevance to evaluating TTP programmes' impact. However, these questions require independent validation in a larger and systematic sample of relevant modeling studies which have appeared in later stages of the pandemic. [ABSTRACT FROM AUTHOR]

Nile tilapia (Oreochromis niloticus) is among the most farmed finfish worldwide, distributed across different environmental conditions. Its wide distribution has mainly been facilitated by several breeding programs and widespread dissemination of genetically improved strains. In the first Nile tilapia study exploiting a whole‐genome pooled sequencing (Poolseq) approach, we identified the genetic structure and signatures of selection in diverse, farmed Nile tilapia populations, with a particular focus on the GIFT strain, developed in the 1980s, and currently managed by WorldFish (GIFTw). We also investigated important farmed strains from The Philippines and Africa. Using both SNP array data and Poolseq SNPs, we characterized the population structure of these samples. We observed the greatest separation between the Asian and African populations and greater admixture in the Asian populations than in the African ones. We also established that the SNP array data were able to successfully resolve relationships between these diverse Nile tilapia populations. The Poolseq data identified genomic regions with high levels of differentiation (FST) between GIFTw and the other populations. Gene ontology terms associated with mesoderm development were significantly enriched in the genes located in these regions. A region on chromosome Oni06 was genetically differentiated in pairwise comparisons between GIFTw and all other populations. This region contains genes associated with muscle‐related traits and overlaps with a previously published QTL for fillet yield, suggesting that these traits may have been direct targets for selection on GIFT. A nearby region was also identified using XP‐EHH to detect genomic differentiation using the SNP array data. Genomic regions with high or extended homozygosity within each population were also identified. This study provides putative genomic landmarks associated with the recent domestication process in several Nile tilapia populations, which could help to inform their genetic management and improvement. [ABSTRACT FROM AUTHOR]

Reducing harmful aggressive behaviour remains a major challenge in pig production. Social network analysis (SNA) showed the potential in providing novel behavioural traits that describe the direct and indirect role of individual pigs in pen-level aggression. Our objectives were to (1) estimate the genetic parameters of these SNA traits, and (2) quantify the genetic associations between the SNA traits and commonly used performance measures: growth, feed intake, feed efficiency, and carcass traits. The animals were video recorded for 24 h post-mixing. The observed fighting behaviour of each animal was used as input for the SNA. A Bayesian approach was performed to estimate the genetic parameters of SNA traits and their association with the performance traits. The heritability estimates for all SNA traits ranged from 0.01 to 0.35. The genetic correlations between SNA and performance traits were non-significant, except for weighted degree with hot carcass weight, and for both betweenness and closeness centrality with test daily gain, final body weight, and hot carcass weight. Our results suggest that SNA traits are amenable for selective breeding. Integrating these traits with other behaviour and performance traits may potentially help in building up future strategies for simultaneously improving welfare and performance in commercial pig farms. [ABSTRACT FROM AUTHOR]

Pig breeding programs worldwide continue to focus on both productivity and robustness. This selection emphasis has to be accompanied by provision of better-quality environments to pigs to improve performance and to enhance health and welfare of pigs. Definition of broader breeding objectives that include robustness traits in addition to production traits is the first step in the development of selection strategies for productivity and robustness. An approach has been presented which facilitates extension of breeding objectives. Post-weaning survival, maternal genetic effects for growth as an indicator of health status and sow mature weight are examples of robustness traits. Further, breeding objectives should be defined for commercial environments and selection indexes should account for genotype by environment interactions (GxE). Average performances of groups of pigs have been used to quantify the additive effects of multiple environmental factors on performance of pigs. For growth, GxE existed when environments differed by 60 g/day between groups of pigs. This environmental variation was observed even on well managed farms. Selection for improved health of pigs should focus on disease resistance to indirectly reduce pathogen loads on farms and on disease resilience to improve the ability of pigs to cope with infection challenges. Traits defining disease resiliencemaybe based on performance andimmune measures, disease incidence or survival rates of pigs. Residual feed intake is a trait that quantifies feed efficiency. The responses of divergent selection lines for residual feed intake to various environmental challenges were often similar or even favourable for the more efficient, low residual feed intake line. These somewhat unexpected results highlight the need to gain a better understanding of the metabolic differences between more or less productive pigs. These physiological differences lead to interactions between the genetic potential of pigs for productivity and robustness and the prevalence of specific environmental conditions. [ABSTRACT FROM AUTHOR]

Social network analysis (SNA) has provided novel traits that describe the role of individual pigs in aggression. The objectives were to (1) estimate the genetic parameters for these SNA traits, (2) quantify the genetic association between SNA and skin lesion traits, and (3) investigate the possible response to selection for SNA traits on skin lesion traits. Pigs were video recorded for 24 h post-mixing. The observed fight and bullying behaviour of each animal was used as input for the SNA. Skin lesions were counted on different body parts at 24 h (SL24h) and 3 weeks (SL3wk) post-mixing. A Bayesian approach estimated the genetic parameters of SNA traits and their association with skin lesions. SNA traits were heritable (h2 = 0.09 to 0.26) and strongly genetically correlated (rg > 0.88). Positive genetic correlations were observed between all SNA traits and anterior SL24h, except for clustering coefficient. Our results suggest that selection for an index that combines the eigenvector centrality and clustering coefficient could potentially decrease SL24h and SL3wk compared to selection for each trait separately. This study provides a first step towards potential integration of SNA traits into a multi-trait selection index for improving pigs' welfare. [ABSTRACT FROM AUTHOR]

Recent breakthroughs in gene-editing technologies that can render individual animals fully resistant to infections may offer unprecedented opportunities for controlling future epidemics in farm animals. Yet, their potential for reducing disease spread is poorly understood as the necessary theoretical framework for estimating epidemiological effects arising from gene-editing applications is currently lacking. Here, we develop semistochastic modeling approaches to investigate how the adoption of gene editing may affect infectious disease prevalence in farmed animal populations and the prospects and time scale for disease elimination. We apply our models to the porcine reproductive and respiratory syndrome (PRRS), one of the most persistent global livestock diseases to date. Whereas extensive control efforts have shown limited success, recent production of gene-edited pigs that are fully resistant to the PRRS virus have raised expectations for eliminating this deadly disease. Our models predict that disease elimination on a national scale would be difficult to achieve if gene editing was used as the only disease control. However, from a purely epidemiological perspective, disease elimination may be achievable within 3 to 6 y, if gene editing were complemented with widespread and sufficiently effective vaccination. Besides strategic distribution of genetically resistant animals, several other key determinants underpinning the epidemiological impact of gene editing were identified. [ABSTRACT FROM AUTHOR]

Background Improvement of feed efficiency in pigs is of great economical and environmental interest and contributes to use limited resources efficiently to feed the world population. Genome scans for feed efficiency traits are of importance to reveal the underlying biological causes and increase the rate of genetic gain. The aim of this study was to determine the genomic architecture of feed efficiency measured by residual energy intake (REI), in association with production, feed conversion ratio (FCR) and nitrogen excretion traits through the identification of quantitative trait loci (QTL) at different stages of growth using a three generation full-sib design population which originated from a cross between Pietrain and a commercial dam line. Results Six novel QTL for REI were detected explaining 2.7-6.1% of the phenotypic variance in REI. At growth from 60-90 kg body weight (BW), a QTL with a significant dominance effect was identified for REI on SSC14, at a similar location to the QTL for feed intake and nitrogen excretion traits. At growth from 90-120 kg BW, three QTL for REI were detected on SSC2, SSC4 and SSC7 with significant additive, imprinting and additive effects, respectively. These QTL (except for the imprinted QTL) were positionally overlapping with QTL for FCR and nitrogen excretion traits. During final growth (120-140 kg BW), a further QTL for REI was identified on SSC8 with significant additive effect, which overlapped with QTL for nitrogen excretion. During entire analysed growth (60-140 kg BW), a novel additive QTL for REI on SSC4 was observed, with no overlapping with QTL for any other traits considered. Conclusions The occurrence of only one overlapping QTL of REI with feed intake suggests that only a small proportion of the variance in REI was explained by change in feed intake, whereas four overlapping QTL of REI with those of nitrogen excretion traits suggests that mostly underlying factors of feed utilisation such as metabolism and protein turnover were the reason for change in REI. Different QTL for REI were identified at different growth stages, indicating that different genes are responsible for efficiency in feed utilisation at different stages of growth. [ABSTRACT FROM AUTHOR]

Abstract: Numerous quantitative trait loci (QTL) have been identified for growth and feed intake in pigs, however, there are currently no reports of interactions between QTL (epistasis) for these traits at different stages of growth. A genomic scan for epistatic QTL was conducted on animals from a three generation full-sib population, created by crossing Pietrain sires with a crossbred dam line. All types of two-locus interactions were fitted in the model using Cockerham''s decomposition, by regressing on a linear combination of the individual QTL origin probabilities. This study is the first to report epistatic QTL for growth, feed intake and chemical body composition in pigs. Eighteen significant epistatic QTL pairs were identified, seven affecting growth, six affecting feed intake or food conversion ratio, and five affecting chemical body composition. Most interacting QTL resided on different chromosomes; only two were located on the same chromosome. The identified QTL pairs explained substantial proportions of the phenotypic variance, from 5% to 10.3%. All types of digenic epistatic effects were identified with the additive-by-additive effect being the most prevalent. These findings suggest that epistasis is important in the genomic regulation of growth, feed intake and chemical body composition. Furthermore, interactions occur between different pairs of epistatic QTL for the same trait depending on the growth stage, increasing the complexity of genomic networks. This agrees with studies on gene expression levels which showed that those are time and tissue dependent. [Copyright &y& Elsevier]

Abstract: The aim of the research was to gain a better understanding of the genomic regulation of meat quality by investigating individual and epistatic QTL in a three-generation full-sib population (Pietrain×crossbred dam line). In total, 386 animals were genotyped for 96 markers. Analysed traits included pH, reflectance value, conductivity, and meat colour. Thirteen significant individual QTL were identified. The most significant QTL were detected on SSC1 and SSC9 for pH, on SSC4 for meat colour, and on SSC8 for conductivity, accounting for 3.4% to 4.7% of the phenotypic variance. Nine significant epistatic QTL pairs were detected accounting for between 5.7% and 10.9% of the phenotypic variance. Epistatic QTL pairs showing the largest effects were for reflectance value between two locations of SSC4, and for pH between SSC10 and SSC13, explaining 9.5% and 10.9% of the phenotypic variance, respectively. This study indicates that meat quality traits are influenced by numerous QTL as well as a complex network of interactions. [ABSTRACT FROM AUTHOR]

The present study focused on the identification of epistatic QTL pairs for body composition traits (carcass cut, lean tissue, and fat tissue weights) measured at slaughter weight (140 kg of BW) in a 3-generation full-sib population developed by crossing Pietrain sires with a crossbred dam line. Depending on the trait, phenotypic observations were available for 306 to 315 F2 animals. For the QTL analysis, 386 animals were genotyped for 88 molecular markers covering chromosomes SSC1, SSC2, SSC4, SSC6, SSC7, SSC8, SSC9, SSC1O, SSC13, and SSC14. In total, 23 significant epistatic QTL pairs were identified, with the additive x additive genetic interaction being the most prevalent. Epistatic QTL were identified across all chromosomes except for SSC13, and epistatic QTL pairs accounted for between 5.8 and 10.2% of the phenotypic variance. Seven epistatic QTL pairs were between QTL that resided on the same chromosome, and 16 were between QTL that resided on different chromosomes. Sus scrofa chromosome 1, SSC2, SSC4, SSC6, SSC8, and SSC9 harbored the greatest number of epistatic QTL. The epistatic QTL pair with the greatest effect was for the entire loin weight between 2 locations on SSC7, explaining 10.2% of the phenotypic variance. Epistatic associations were identified between regions of the genome that contain the IGF-2 or melanocortin-4 receptor genes, with QTL residing in other genomic locations. Quantitative trait loci in the region of the rnelanocortin-4 receptor gene and on SSC7 showed significant positive dominance effects for entire belly weight, which were offset by negative dominance × dominance interactions between these QTL. In contrast, the QTL in the region of the IGF-2 gene showed significant negative dominance effects for entire ham weight, which were largely overcompensated for by positive additive × dominance genetic effects with a QTL on SSC9. The study shows that epistasis is of great importance for the genomic regulation of body composition in pigs and contributes substantially to the variation in complex traits. [ABSTRACT FROM AUTHOR]

In this study, quantitative trait loci (QTL) for chemical and physical body composition, growth and feed intake in pigs were identified in a three-generation full-sib population, developed by crossing Pietrain sires with a commercial dam line. Phenotypic data from 315 F2 animals were available for protein and lipid deposition measured in live animals by the deuterium dilution technique at 30-, 60-, 90-, 120- and 140-kg body weight. At 140-kg body weight, carcass characteristics were measured by the AutoFOM grading system and after dissection. Three hundred and eighty-six animals from 49 families were genotyped for 51 molecular markers covering chromosomes SSC2, SSC4, SSC8, SSC9, SSC10 and SSC14. Novel QTL for protein (lipid) content at 60-kg body weight and protein (lipid) accretion from 120 to 140 kg were detected on SSC9 near several previously detected QTL for lean and fat tissue in neck, shoulder and ham cuts. Another QTL for lipid accretion was found on SSC8, closely associated with a QTL for intramuscular fat content. QTL for daily feed intake were detected on SSC2 and SSC10. The favourable allele of a QTL for food conversion ratio (FCR) on SSC2 was associated with alleles for increased lean tissue and decreased fat tissue. Because no QTL for growth rate were found in the region, the QTL for FCR is most likely due to a change in body composition. These QTL provide insights into the genomic regulation of chemical or physical body composition and its association with feed intake, feed efficiency and growth. [ABSTRACT FROM AUTHOR]

Imaging technology can aid the automatic extraction of measurements from beef carcasses, which can be used for objective grading. Many abattoirs, however, rely on manual grading due to the required infrastructure and cost, making technology unfeasible. This study explores 3-dimensional (3D) imaging technology, requiring limited infrastructure, and its ability to predict carcass weight, conformation class and fat class for non-invasive, objective classification. Time-of-flight near-infrared cameras captured 3-dimensional point clouds of beef carcasses, on-line in one commercial abattoir in Scotland, over a 6-month period. Thirty-five 3D images were captured per carcass and processed using machine vison software. Seventy-four measurements were extracted from each point cloud. Removal of extreme outliers resulted in 285,109 datapoints for 17,250 carcasses. Coefficients of variation (CV) for each measurement on a per-animal basis were low and consistent, and measurements were averaged across images. Using a training and validation dataset (70:30), multiple linear regression models predicted EUROP conformation class, fat class, and carcass weight. Stepwise models included fixed effects (sex, breed type, kill date (and cold carcass weight for conformation and fat class)), and 3D image measurements. Including 3D measurements resulted in prediction accuracies of 70%, 50% and 23% for cold carcass weight, conformation, and fat class respectively. Mapping predictions on the traditional EUROP grid used in the UK showed that 99% of conformation classes and 93% of fat classes were classified within the correct or neighbouring grade. The results of this study indicate the potential for non-invasive, in-abattoir technology requiring limited infrastructure to predict carcass traits objectively. • Three-dimensional measurements (n = 74) were extracted from images of beef carcasses. • Linear regression models predicted EUROP grades and cold carcass weight (CCW). • Accuracies = 70%, 52% and 23% for CCW, conformation and fat class respectively. [ABSTRACT FROM AUTHOR]

Individuals differ widely in their contribution to the spread of infection within and across populations. Three key epidemiological host traits affect infectious disease spread: susceptibility (propensity to acquire infection), infectivity (propensity to transmit infection to others) and recoverability (propensity to recover quickly). Interventions aiming to reduce disease spread may target improvement in any one of these traits, but the necessary statistical methods for obtaining risk estimates are lacking. In this paper we introduce a novel software tool called SIRE (standing for "Susceptibility, Infectivity and Recoverability Estimation"), which allows for the first time simultaneous estimation of the genetic effect of a single nucleotide polymorphism (SNP), as well as non-genetic influences on these three unobservable host traits. SIRE implements a flexible Bayesian algorithm which accommodates a wide range of disease surveillance data comprising any combination of recorded individual infection and/or recovery times, or disease diagnostic test results. Different genetic and non-genetic regulations and data scenarios (representing realistic recording schemes) were simulated to validate SIRE and to assess their impact on the precision, accuracy and bias of parameter estimates. This analysis revealed that with few exceptions, SIRE provides unbiased, accurate parameter estimates associated with all three host traits. For most scenarios, SNP effects associated with recoverability can be estimated with highest precision, followed by susceptibility. For infectivity, many epidemics with few individuals give substantially more statistical power to identify SNP effects than the reverse. Importantly, precise estimates of SNP and other effects could be obtained even in the case of incomplete, censored and relatively infrequent measurements of individuals' infection or survival status, albeit requiring more individuals to yield equivalent precision. SIRE represents a new tool for analysing a wide range of experimental and field disease data with the aim of discovering and validating SNPs and other factors controlling infectious disease transmission. Author summary: Effective approaches to reduce the spread of infectious disease transmission in populations are urgently needed. Reduction in disease spread is most effectively achieved by reducing, separately or in combination, individual (i) "susceptibility", i.e. the relative risk to become infected when exposed to infectious individuals or material, (ii) "infectivity", i.e. the propensity to transmit infection to others when infected, and/or by (iii) improving "recoverability", i.e. the propensity to recover. However, to date it is impossible to assess how these three key epidemiological traits controlling disease transmission in a population are regulated by specific genes or interventions, as the necessary statistical methods for estimating genetic and non-genetic effects associated with these three traits from available disease surveillance data don't exist. This paper introduces a novel statistical method that can estimate, for the first time, genetic and non-genetic effects for host susceptibility, infectivity and recoverability simultaneously from a wide range of realistic disease surveillance data. The method has been incorporated into a user-friendly, freely available software tool called SIRE. SIRE can be applied to a range of experimental and field data and will help to move disease control significantly forward by simultaneously targeting multiple host traits affecting infectious disease spread. [ABSTRACT FROM AUTHOR]

Contest behaviour, and in particular the propensity to attack an unfamiliar conspecific, is influenced by an individual's aggressiveness, as well as by experience of winning and losing (so called 'winner–loser effects'). Individuals vary in aggressiveness and susceptibility to winner–loser effects but the relationship between these drivers of contest behaviour has been poorly investigated. Here we hypothesise that the winner–loser effect on initiation of agonistic behaviour (display, non-damaging aggression, biting and mutual fighting) is influenced by aggressiveness. Pigs (n = 255) were assayed for aggressiveness (tendency to attack in resident−intruder tests) and then experienced two dyadic contests (age 10 and 13 weeks). Agonistic behaviour, up to reciprocal fighting, in contest 2 was compared between individuals of different aggressiveness in the RI test and experiences of victory or defeat in contest 1. Winner–loser effects were more influential than aggressiveness in determining initiation of agonistic behaviour. After accruing more skin lesions in contest 1, individuals were less likely to engage in escalated aggression in contest 2. The interaction between aggressiveness and winner–loser experience did not influence contest behaviour. The results suggest that aggressiveness does not compromise learning from recent contest experience and that reducing aggressiveness is unlikely to affect how animals experience winning and losing. [ABSTRACT FROM AUTHOR]

• Vaccination in this experiment did not protect pigs from becoming infected through contact with infected animals. • Vaccination did have a beneficial impact on the within-group transmission dynamics and resulted in a lower R 0. • The presence of pigs with no serological response only marginally affected transmission dynamics. • Biosecurity and other measures are needed to lower the R 0 below 1.0. Vaccination is the main tool for controlling infectious diseases in livestock. Yet current vaccines only provide partial protection raising concerns about vaccine effectiveness in the field. Two successive transmission trials were performed involving 52 pigs to evaluate the effectiveness of a Porcine Reproductive and Respiratory Syndrome (PRRS) vaccinal strain candidate against horizontal transmission of a virulent heterologous strain. PRRS virus, above the specified limit of detection, was observed in serum and nasal secretions for all but one pig (the exception only tested positive for serum), indicating that vaccination did not protect pigs from becoming infected and shedding the heterologous strain. However, vaccination delayed the onset of viraemia, reduced the duration of shedding and significantly decreased viral load throughout infection. Serum antibody profiles indicated that 4 out of 13 (31%) vaccinates in one trial had no serological response (NSR). A Bayesian epidemiological model was fitted to the data to assess the impact of vaccination and presence of NSRs on PRRS virus transmission dynamics. Despite little evidence for reduction in the transmission rate, vaccinated animals were on average slower to become infectious, experienced a shorter infectious period and recovered faster. The overall PRRSV transmission potential, represented by the reproductive ratio R 0 was lower for the vaccinated animals, although there was substantial overlap in the credibility intervals for both groups. Model selection suggests that transmission parameters of vaccinated pigs with NSR were more similar to those of unvaccinated animals. The presence of NSRs in a population, however, seemed to only marginally affect the transmission dynamics. The results suggest that even when vaccination can't prevent infection, it can still have beneficial impacts on the transmission dynamics and contribute to reducing a herd's R 0. However, biosecurity and other measures need to be considered to decrease contact rates and lower R 0 below 1. [ABSTRACT FROM AUTHOR]

Many livestock and human vaccines are leaky because they block symptoms but do not prevent infection or onward transmission. This leakiness is concerning because it increases vaccination coverage required to prevent disease spread and can promote evolution of increased pathogen virulence. Despite leakiness, vaccination may reduce pathogen load, affecting disease transmission dynamics. However, the impacts on post-transmission disease development and infectiousness in contact individuals are unknown. Here, we use transmission experiments involving Marek disease virus (MDV) in chickens to show that vaccination with a leaky vaccine substantially reduces viral load in both vaccinated individuals and unvaccinated contact individuals they infect. Consequently, contact birds are less likely to develop disease symptoms or die, show less severe symptoms, and shed less infectious virus themselves, when infected by vaccinated birds. These results highlight that even partial vaccination with a leaky vaccine can have unforeseen positive consequences in controlling the spread and symptoms of disease. "Leaky" vaccination of chickens infected with Marek"s disease virus reduced symptoms and lowered mortality in the unvaccinated contact birds infected by them. The cause was transmission of lower virus loads from vaccinated than unvaccinated birds; this benefit of leaky vaccination is rarely taken into consideration. [ABSTRACT FROM AUTHOR]

Vaccines remain one of the main tools to control infectious diseases in domestic livestock. Although a plethora of veterinary vaccines are on the market and routinely applied to protect animals against infection with particular pathogens, the disease in question often continues to persist, sometimes at high prevalence. The limited effectiveness of certain vaccines in the field leaves open questions regarding the required properties that an effective vaccine should have, as well as the most efficient vaccination strategy for achieving the intended goal of vaccination programmes. To date a systematic approach for studying the combined effects of different types of vaccines and vaccination strategies is lacking. In this paper, we develop a theoretical framework for modelling the epidemiological consequences of vaccination with imperfect vaccines of various types, administered using different strategies to herds with different replacement rates and heterogeneity in vaccine responsiveness. Applying the model to the Porcine Reproductive and Respiratory Syndrome (PRRS), which despite routine vaccination remains one of the most significant endemic swine diseases worldwide, we then examine the influence of these diverse factors alone and in combination, on within-herd virus transmission. We derive threshold conditions for preventing infection invasion in the case of imperfect vaccines inducing limited sterilizing immunity. The model developed in this study has practical implications for the development of vaccines and vaccination programmes in livestock populations not only for PRRS, but also for other viral infections primarily transmitted by direct contact. [ABSTRACT FROM AUTHOR]

Background: Understanding what determines the between-host variability in infection dynamics is a key issue to better control the infection spread. In particular, pathogen clearance is desirable over rebounds for the health of the infected individual and its contact group. In this context, the Porcine Respiratory and Reproductive Syndrome virus (PRRSv) is of particular interest. Numerous studies have shown that pigs similarly infected with this highly ubiquitous virus elicit diverse response profiles. Whilst some manage to clear the virus within a few weeks, others experience prolonged infection with a rebound. Despite much speculation, the underlying mechanisms responsible for this undesirable rebound phenomenon remain unclear. Results: We aimed at identifying immune mechanisms that can reproduce and explain the rebound patterns observed in PRRSv infection using a mathematical modelling approach of the within-host dynamics. As diverse mechanisms were found to influence PRRSv infection, we established a model that details the major mechanisms and their regulations at the between-cell scale. We developed an ABC-like optimisation method to fit our model to an extensive set of experimental data, consisting of non-rebounder and rebounder viremia profiles. We compared, between both profiles, the estimated parameter values, the resulting immune dynamics and the efficacies of the underlying immune mechanisms. Exploring the influence of these mechanisms, we showed that rebound was promoted by high apoptosis, high cell infection and low cytolysis by Cytotoxic T Lymphocytes, while increasing neutralisation was very efficient to prevent rebounds. Conclusions: Our paper provides an original model of the immune response and an appropriate systematic fitting method, whose interest extends beyond PRRS infection. It gives the first mechanistic explanation for emergence of rebounds during PRRSv infection. Moreover, results suggest that vaccines or genetic selection promoting strong neutralising and cytolytic responses, ideally associated with low apoptotic activity and cell permissiveness, would prevent rebound. [ABSTRACT FROM AUTHOR]

Summary: Robustness has become a highly desirable breeding goal in the globalized agricultural market. Both genotype‐by‐environment interaction (G × E) and micro‐environmental sensitivity are important robustness components of aquaculture production, in which breeding stock is often disseminated to different environments. The objectives of this study were (i) to quantify the degree of G × E by assessing the growth performance of Genetically Improved Farmed Tilapia (GIFT) across three countries (Malaysia, India and China) and (ii) to quantify the genetic heterogeneity of environmental variance for body weight at harvest (BW) in GIFT as a measure of micro‐environmental sensitivity. Selection for BW was carried out for 13 generations in Malaysia. Subsets of 60 full‐sib families from Malaysia were sent to China and India after five and nine generations respectively. First, a multi‐trait animal model was used to analyse the BW in different countries as different traits. The results indicate a strong G × E. Second, a genetically structured environmental variance model, implemented using Bayesian inference, was used to analyse micro‐environmental sensitivity of BW in each country. The analysis revealed the presence of genetic heterogeneity of both BW and its environmental variance in all environments. The presence of genetic variation in residual variance of BW implies that the residual variance can be modified by selection. Incorporating both G × E and micro‐environmental sensitivity information may help in selecting robust genotypes with high performance across environments and resilience to environmental fluctuations. [ABSTRACT FROM AUTHOR]

There is increasing recognition that genetic diversity can affect the spread of diseases, potentially affecting plant and livestock disease control as well as the emergence of human disease outbreaks. Nevertheless, even though computational tools can guide the control of infectious diseases, few epidemiological models can simultaneously accommodate the inherent individual heterogeneity in multiple infectious disease traits influencing disease transmission, such as the frequently modeled propensity to become infected and infectivity, which describes the host ability to transmit the infection to susceptible individuals. Furthermore, current quantitative genetic models fail to fully capture the heritable variation in host infectivity, mainly because they cannot accommodate the nonlinear infection dynamics underlying epidemiological data. We present in this article a novel statistical model and an inference method to estimate genetic parameters associated with both host susceptibility and infectivity. Our methodology combines quantitative genetic models of social interactions with stochastic processes to model the random, nonlinear, and dynamic nature of infections and uses adaptive Bayesian computational techniques to estimate the model parameters. Results using simulated epidemic data show that our model can accurately estimate heritabilities and genetic risks not only of susceptibility but also of infectivity, therefore exploring a trait whose heritable variation is currently ignored in disease genetics and can greatly influence the spread of infectious diseases. Our proposed methodology offers potential impacts in areas such as livestock disease control through selective breeding and also in predicting and controlling the emergence of disease outbreaks in human populations. [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate the genetic relationships between skin lesion traits in group housed growing pigs as a measure of short-(in a newly mixed group) and long-(in a socially stable group) term aggression and commonly used commercial performance measures: growth, feed intake, feed efficiency, and carcass traits. Data on 2,413 growing pigs (138 groups) were available. Pigs were mixed into new social groups of 18 animals, and skin lesions were counted 24 h (SL24h) and 5 wk (SL5wk) postmixing. The animal model was used to estimate genetic parameters for skin lesion traits, test daily gain, lifetime daily gain, daily feed intake, feed efficiency (calculated as test daily gain divided by daily feed intake), loin depth, back fat, and HCW. Skin lesions had a heritable component, ranging from 0.08 for anterior SL24h to 0.22 for central SL5wk and would, therefore, be suitable as a method of phenotyping aggression for selection purposes. Significant positive genetic correlations were found between SL24h and SL5wk (0.46 to 0.81). Positive genetic correlations were also found between SL24h (central and posterior body regions) or SL5wk (all body regions) and the production traits lifetime daily gain, test daily gain, and HCW (0.29 to 0.54). Central SL24h, anterior SL5wk, and posterior SL5wk were found to correlate positively with feed efficiency (0.39 to 0.50), suggesting that pigs with more lesions convert feed more efficiently. Where significant, the magnitude of phenotypic correlations was low but positive (0.07 to 0.10). These results suggest that, genetically, animals that receive many lesions show improved performance compared to those with few lesions, except for anterior SL24h, which had previously been shown to be genetically positively correlated with the initiation of nonreciprocal attacks. It may, therefore, be possible, via selection against anterior skin lesions at mixing, to reduce this form of 1-sided aggression without adversely affecting production traits. [ABSTRACT FROM AUTHOR]

Mixing of growing pigs results in aggressive contests between group members. As aggression serves to establish dominance relationships, it is possible that increased initial aggression may facilitate the formation of social hierarchies. The objective of the study was to investigate whether there is a phenotypic link between behavioural traits of aggression at mixing and increased long-term group social stability. Aggressive behavioural traits were recorded for 24 h after mixing, whereas the numbers of skin lesions (anterior, central and posterior) were obtained 24 h (SL24h) and 3 weeks post-mixing (SL3wk) for 1,166 pigs. At the group level, aggressive behavioural traits were positively correlated with anterior SL24h (0.34 to 0.67; P < 0.01) at mixing, and negatively with central SL3wk (−0.28 to −0.38; P < 0.01) in the stable group. At the individual animal level, most behavioural traits of aggressiveness correlated positively with SL24h (0.09 to 0.53; P < 0.001), whereas the opposite associations were found for SL3wk (−0.06 to −0.14; P < 0.05). Within aggressive cohorts, animals with a high fight success rate received slightly fewer SL24h than equally aggressive, but unsuccessful pen mates, while animals that avoided aggression received the fewest SL24h. Corresponding associations were reversed in the stable group. These results provide evidence that increased aggression at mixing may aid stable hierarchy formation. This raises an ethical dilemma in pigs production, but potentially also in other species, that increased acute aggression during mixing may actually decrease chronic aggression in groups and thus benefit the long term welfare of the group. [ABSTRACT FROM AUTHOR]

Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically significant viral diseases facing the global swine industry. Viremia profiles of PRRS virus challenged pigs reflect the severity and progression of infection within the host and provide crucial information for subsequent control measures. In this study we analyse the largest longitudinal PRRS viremia dataset from an in-vivo experiment. The primary objective was to provide a suitable mathematical description of all viremia profiles with biologically meaningful parameters for quantitative analysis of profile characteristics. The Wood's function, a gamma-type function, and a biphasic extended Wood's function were fit to the individual profiles using Bayesian inference with a likelihood framework. Using maximum likelihood inference and numerous fit criteria, we established that the broad spectrum of viremia trends could be adequately represented by either uni- or biphasic Wood's functions. Three viremic categories emerged: cleared (uni-modal and below detection within 42 days post infection(dpi)), persistent (transient experimental persistence over 42 dpi) and rebound (biphasic within 42 dpi). The convenient biological interpretation of the model parameters estimates, allowed us not only to quantify inter-host variation, but also to establish common viremia curve characteristics and their predictability. Statistical analysis of the profile characteristics revealed that persistent profiles were distinguishable already within the first 21 dpi, whereas it is not possible to predict the onset of viremia rebound. Analysis of the neutralizing antibody(nAb) data indicated that there was a ubiquitous strong response to the homologous PRRSV challenge, but high variability in the range of cross-protection of the nAbs. Persistent pigs were found to have a significantly higher nAb cross-protectivity than pigs that either cleared viremia or experienced rebound within 42 dpi. Our study provides novel insights into the nature and degree of variation of hosts' responses to infection as well as new informative traits for subsequent genomic and modelling studies. [ABSTRACT FROM AUTHOR]

Reducing disease prevalence through selection for host resistance offers a desirable alternative to chemical treatment. Selection for host resistance has proven difficult, however, due to low heritability estimates. These low estimates may be caused by a failure to capture all the relevant genetic variance in disease resistance, as genetic analysis currently is not taylored to estimate genetic variation in infectivity. Host infectivity is the propensity of transmitting infection upon contact with a susceptible individual, and can be regarded as an indirect effect to disease status. It may be caused by a combination of physiological and behavioural traits. Though genetic variation in infectivity is difficult to measure directly, Indirect Genetic Effect (IGE) models, also referred to as associative effects or social interaction models, allow the estimation of this variance from more readily available binary disease data (infected/non-infected). We therefore generated binary disease data from simulated populations with known amounts of variation in susceptibility and infectivity to test the adequacy of traditional and IGE models. Our results show that a conventional model fails to capture the genetic variation in infectivity inherent in populations with simulated infectivity. An IGE model, on the other hand, does capture some of the variation in infectivity. Comparison with expected genetic variance suggests that there is scope for further methodological improvement, and that potential responses to selection may be greater than values presented here. Nonetheless, selection using an index of estimated direct and indirect breeding values was shown to have a greater genetic selection differential and reduced future disease risk than traditional selection for resistance only. These findings suggest that if genetic variation in infectivity substantially contributes to disease transmission, then breeding designs which explicitly incorporate IGEs might help reduce disease prevalence. [ABSTRACT FROM AUTHOR]

Abstract: Technological meat quality is a significant economic factor in pork production, and numerous publications have shown that it is strongly influenced both by genetic status and by rearing and slaughter conditions. The quality of meat is often described by meat pH at different times postmortem, as well as by color and drip loss. A meta-analysis based on a database built from 27 studies corresponding to a total of 6526 animals classified was carried out. The purpose of this meta-analysis was to study the effect of fasting, lairage and transport durations on four main attributes of the technological pork meat quality. A Bayesian hierarchical meta-regression approach was adopted. The results of our meta-analysis showed that fasting time had a significant effect on pH measured 24h post-mortem (pHu) and drip loss (DL) measured in longissimus muscle. While, lairage affected only the pHu in semimembranosus muscle. Interestingly, we found that DL was the lone attribute that was affected by transport time and its interaction with fasting time. [Copyright &y& Elsevier]

Abstract: Meta-analyses have been carried out to quantify the effect of dietary vitamin E on α-tocopherol accumulation and on lipid oxidation in porcine M. longissimus. Published results of 13 (vitamin E accumulation) and 10 (lipid oxidation) experiments respectively were used for the analyses. After a number of standardization procedures, a nonlinear relationship was found between the supplementary vitamin E and the accumulation of α-tocopherol in pork which approached a maximum value of 6.4μg/g tissue. Pork lipid oxidation levels were described in terms of Thiobarbituric Acid Reacting Substances (TBARS) values. The statistical analysis revealed significant effect of vitamin E dose, muscle α-tocopherol concentration and supplementation time on TBARS, resulting in two prediction models for lipid oxidation. Meta-analysis has proven to be a valuable tool for combining results from previous studies to quantify the effects of dietary vitamin E. Further studies, carried out with standardized experimental protocols would be beneficial for model validation and to increase the predictive power of the derived models. [ABSTRACT FROM AUTHOR]

Technological meat quality is a significant economic factor in pork production, and numerous publications have shown that it is strongly influenced both by genetic status and by rearing and slaughter conditions. The quality of meat is often described by irieat pH at different times postmortem, as well as by color and drip loss, whereas carcass quality is often characterized by lean percentage. A meta-analysis of findings relating to 3,530 pigs reported in 23 publications was carried out to assess the effects of the halothane gene, sex, breed, and slaughter weight of animals on 7 selected variables: pH at 45 mm postmortem, ultimate pH, reflectance (L*-value), redness (a*-value), yellowness (b*-value), drip loss, and lean percentage. Two statistical methods were used in the meta-analysis: the method of effect size and the better known random effects model. The method of effect size was associated with Markov chain Monte Carlo techniques for implementing Bayesian hierarchical models to avoid the problems of limited data and publication bias. The results of our meta-analysis showed that the halothane genotype had a significant effect on all analyzed pork quality variables. Between-study variance was evaluated with the Cochran (1954) Q-test of heterogeneity. Meta-regression was used to explain this variance, with covariates such as breed, sex, slaughter weight, and fasting duration being integrated into different regression models. The halothane gene effect was associated with the breed effect only for the following variables: L*-value, b*-value, and drip loss. Slaughter weight contributed significantly only to the explanation of differences in ultimate pH between homozygous genotypes. In response to inconsistencies reported in the literature regarding the difference between the genotypes NN and Nn, results of the meta-analysis showed that the difference between these 2 genotypes was significant for all the analyzed variables except the a*-value. [ABSTRACT FROM AUTHOR]

Aggression between unfamiliar commercial pigs is common and likely invokes strong emotions in contestants. Furthermore, contest outcomes affect subsequent aggressive behaviour, suggesting a potential lasting influence on affective state. Here we used a combination of qualitative and quantitative methods to assess the emotional expression of pigs in agonistic encounters. We investigated how recent victory or defeat influences emotions expressed in a subsequent contest, and the role of aggressiveness as a personality trait in emotional expression. We observed the pre-escalation contest behaviour (second contest; age 13 wks) in animals of different aggressiveness (categorised using two resident intruder tests as Agg+ or Agg-, age 9 wks), which had recently won or lost a contest (first contest; 10 wks). We measured gaze direction and ear position. Observers watched video clips of the initial 30 s of the second contest and evaluated the emotional expression of 57 pigs (25 contest 1 winners, 32 contest 1 losers) using qualitative behavioural assessment (QBA) with a fixed list of 20 descriptive terms. QBA identified three principal components (PCs), accounting for 68% of the variation: PC1 (agitated/tense to relaxed/content), PC2 (fearful/aimless to confident/enjoying) and PC3 (listless/ indifferent). Agg- pigs and males showed a more positive emotionality (PC2). PC1 and PC3 were unaffected by first contest outcome and aggressiveness. Agg+ pigs were more likely to hold their ears back (X2 =7.8, p = 0.005) during the early contest period. Differences in attention were detected in the contest outcome × aggressiveness interaction (χ24.3, p = 0.04), whereby approaching the opponent was influenced by winning and losing in the Agg- pigs only. QBA and gaze behaviour reveal differences in emotional valence between pigs of different aggressiveness: less aggressive pigs may be more susceptible to the emotional impact of victory and defeat but overall, more aggressive pigs express more negative emotionality at the start of agonistic encounters. [Display omitted] • The emotional expression of pigs meeting a new opponent is influenced by past contest experience. • Prior losers gazed towards the exit gate more than winners. • Aggressive personality influenced ear posture, gaze direction and emotional expressivity. [ABSTRACT FROM AUTHOR]

A transmission trial was carried out using 420 Atlantic salmon (Salmo salar L., parr stage) to simultaneously test the impact of vaccination and selective breeding on the transmission of Infectious salmon anemia virus (ISAV). Genetic difference in disease resistance was based on mortality differences across 15 families (defined by a genomic breeding value (GEBV)) and organised into three groups (low GEBV (LBV), mid GEBV (MBV) and high GEBV (HBV)). Three different shedder groups were infected with ISAV before being placed in tanks (T1 – T18) with naive contact fish (n = 15), one representative from each of the 15 families. The shedder groups included LBV vaccinated (LBV v), LBV not vaccinated (LBV nv) and HBV not vaccinated (HBV nv). The trial was run with two consecutive sets of nine tanks so the infectiousness of the shedder fish could be tested at different stages in their infection process (early (3–9 days post-infection (dpi) versus late (9–15 dpi)). Infection and mortality data of the contact fish were analysed using a Generalised Linear Mixed Model (GLMM) and a Bayesian epidemiological model. Neither vaccination nor genetic resistance prevented transmission, but both lowered the probability of infection in contact fish. Though not statistically significant, the effect of genetic resistance was larger (LBV NV vs HBV NV : odds ratio: 8.35 (0.75–93.36)) than vaccination (LBV NV vs LBV V : odds ratio: 4.52 (0.43–46.99)). There was no difference in the susceptibility of fish with different resistance breeding values, however, significant differences were found in their endurance to ISAV infection, with LBV fish dying 14 days earlier than HBV fish. Mortality as a resistance phenotype in breeding programmes appears to simultaneously improve survival of ISAV infected fish and reduce ISA transmission. However, it would be beneficial to evaluate mucus viral load (MVL) as an additional phenotype to more effectively reduce ISA transmission. • Vaccination and genetic resistance lowered the probability of infection but did not prevent transmission. • The probability of infection was lower for genetic resistance than vaccination. • Fish with different genetic resistance differed in endurance, not susceptibility. • Additional phenotypes more closely associated with transmission should be examined. [ABSTRACT FROM AUTHOR]

Early play fighting mimics later aggression in many species, and may, therefore, be expected to reduce costs from later aggressive interactions. Using social network analysis (SNA) the effect of a central play fighting network position on later skin lesions from aggression was assessed in domestic pigs. Piglets (n = 263) were kept in litter groups or socialised pre-weaning with another litter to enhance play fighting experience. Play fighting was recorded for 1.5 h per day over 6 days pre-weaning. Play fighting network centrality was quantified using measures of individual network position and entire network structure (degree, eigenvector, betweenness, clustering coefficient). Skin lesions from aggression were counted after a dyadic contest and at 24 h and 3 weeks following group mixing. Pigs with play fighting interactions with many partners experienced fewer lesions from the dyadic contest (in-degree, p = 0.01) and tended to received fewer lesions 3 weeks after group mixing (degree, p = 0.088) but no other play fighting centrality measures affected the number of lesions at any point. The benefits of play fighting were therefore limited to specific aggressive social contexts. The tendency of socialised piglets to play fight with non-littermates did not affect subsequent lesions. We advocate the use of SNA over approaches that only consider dyadic interactions to further our understanding of the influence of early social group interactions on later life experience. [ABSTRACT FROM AUTHOR]

Survival during an epidemic is partly determined by host genetics. While quantitative genetic studies typically consider survival as an indicator for disease resistance (an individual's propensity to avoid becoming infected or diseased), mortality rates of populations undergoing an epidemic are also affected by endurance (the propensity of diseased individual to survive the infection) and infectivity (i.e. the propensity of an infected individual to transmit disease). Few studies have demonstrated genetic variation in disease endurance, and no study has demonstrated genetic variation in host infectivity, despite strong evidence for considerable phenotypic variation in this trait. Here we propose an experimental design and statistical models for estimating genetic diversity in all three host traits. Using an infection model in fish we provide, for the first time, direct evidence for genetic variation in host infectivity, in addition to variation in resistance and endurance. We also demonstrate how genetic differences in these three traits contribute to survival. Our results imply that animals can evolve different disease response types affecting epidemic survival rates, with important implications for understanding and controlling epidemics. [ABSTRACT FROM AUTHOR]