Selecting for changes in average "parity curve" pattern of litter size in Large White pigs.

This study aimed to analyse genetic background of variation in reproductive performance between parities of a sow and to investigate selection strategies to change the "parity curve". Total number born (TNB) recorded in Large White sows was provided by Topigs Norsvin. Analysis with basic (BM) and random regression (RRM) models was done in ASReml 4.1. The BM included only a fixed "parity curve", while RRM included 3rd order polynomials for additive genetic and permanent sow effects. Parameters from RRM were used in simulations in SelAction 2.1. Based on Akaike information criterion, RRM was a better model for TNB data. Genetic variance and heritability estimates of TNB from BM and RRM were increasing with parity from parity 2. Genetically, parity 1 is the most different from parities 7 to 10, whereas most similar to parities 2 and 3. This indicates presence of genetic variation to change the "parity curve". Based on simulations, the selection to increase litter size in parity 1 only increases TNB in all parities, but does not change the observed shape of "parity curve", whereas selection for increased TNB in parity 1 and reduced TNB in parity 5 decreases differences between parities, but also reduces overall TNB in all parities. Changing the "parity curve" will be difficult as the genetic and phenotypic relationships between the parities are hard to overcome even when selecting for one parity.

The genetic basis of swine inflammation and necrosis syndrome and its genetic association with post-weaning skin damage and production traits.

The swine inflammation and necrosis syndrome (SINS) is a syndrome visually characterized by the presence of inflamed and necrotic skin at extreme body parts, such as the teats, tail, ears, and claw coronary bands. This syndrome is associated with several environmental causes, but knowledge of the role of genetics is still limited. Moreover, piglets affected by SINS are believed to be phenotypically more susceptible to chewing and biting behaviors from pen mates, which could cause a chronic reduction in their welfare throughout the production process. Our objectives were to 1) investigate the genetic basis of SINS expressed on piglets' different body parts and 2) estimate SINS genetic relationship with post-weaning skin damage and pre and post-weaning production traits. A total of 5,960 two to three-day-old piglets were scored for SINS on the teats, claws, tails, and ears as a binary phenotype. Later, those binary records were combined into a trait defined as TOTAL_SINS. For TOTAL_SINS, animals presenting no signs of SINS were scored as 1, whereas animals showing at least one affected part were scored as 2. Apart from SINS traits, piglets had their birth weight (BW) and weaning weight (WW) recorded, and up to 4,132 piglets were later evaluated for combined skin damage (CSD), carcass backfat (BF), and loin depth (LOD). In the first set of analyses, the heritability of SINS on different body parts was estimated with single-trait animal-maternal models, and pairwise genetic correlations between body parts were obtained from two-trait models. Later, we used four three-trait animal models with TOTAL_SINS, CSD, and an alternative production trait (i.e., BW, WW, LOD, BF) to access trait heritabilities and genetic correlations between SINS and production traits. The maternal effect was included in the BW, WW, and TOTAL_SINS models. The direct heritability of SINS on different body parts ranged from 0.08 to 0.34, indicating that reducing SINS incidence through genetic selection is feasible. The direct genetic correlation between TOTAL_SINS and pre-weaning growth traits (BW and WW) was favorable and negative (from -0.40 to -0.30), indicating that selection for animals genetically less prone to present signs of SINS will positively affect the piglet's genetics for heavier weight at birth and weaning. The genetic correlations between TOTAL_SINS and BF and between TOTAL_SINS and LOD were weak or not significant (-0.16 to 0.05). However, the selection against SINS was shown to be genetically correlated with CSD, with estimates ranging from 0.19 to 0.50. That means that piglets genetically less likely to present SINS signs are also more unlikely to suffer CSD after weaning, having a long-term increase in their welfare throughout the production system.

The swine inflammation and necrosis syndrome (SINS) is visually characterized by the presence of inflamed and necrotic skin at extreme body parts, such as the teats, tail, ears, and claw coronary bands. Piglets affected by this syndrome are considered phenotypically more susceptible to chewing and biting behaviors from pen mates. However, the genetic relationship between SINS and post-weaning skin damage is still unclear. In this study, we aimed to investigate the genetic basis of SINS expressed on piglets' different body parts and to estimate the SINS genetic relationship with skin damage and pre and post-weaning production traits. We showed that SINS on different body parts is heritable and that the direct selection against a combined score of SINS in different body parts (TOTAL_SINS) will favor the piglet's genetics for heavier weight at birth and weaning. However, TOTAL_SINS is not significantly correlated with carcass backfat thickness and loin depth at the piglet genetic level. The direct selection against SINS is genetically correlated with skin damage after weaning, meaning that piglets genetically more prone to present signs of SINS are more likely to receive skin damage later in life.

Impact of Enrichment and Repeated Mixing on Resilience in Pigs.

Resilience, the capacity of animals to be minimally affected by a disturbance or to rapidly bounce back to the state before the challenge, may be improved by enrichment, but negatively impacted by a high allostatic load from stressful management procedures in pigs. We investigated the combined effects of diverging environmental conditions from weaning and repeated mixing to create high allostatic load on resilience of pigs. Pigs were either exposed to barren housing conditions (B) from weaning onwards or provided with sawdust, extra toys, regular access to a "play arena" and daily positive human contact (E). Half of the pigs were exposed to repeated mixing (RM) and the other half to one mixing only at weaning (minimal mixing, MM). To assess their resilience, the response to and recovery from a lipopolysaccharide (LPS) sickness challenge and a Frustration challenge were studied. In addition, potential long-term resilience indicators, i.e. natural antibodies, hair cortisol and growth were measured. Some indications of more favorable responses to the challenges in E pigs were found, such as lower serum reactive oxygen metabolite (dROM) concentrations and a smaller area under the curve of dROM after LPS injection. In the Frustration challenge, E pigs showed less standing alert, escape behaviors and other negative behaviors, a tendency for a smaller area under the curve of salivary cortisol and a lower plasma cortisol level at 1 h after the challenge. Aggression did not decrease over mixings in RM pigs and was higher in B pigs than in E pigs. Repeated mixing did not seem to reduce resilience. Contrary to expectations, RM pigs showed a higher relative growth than MM pigs during the experiment, especially in the week of the challenges. Barren RM pigs showed a lower plasma cortisol concentration than barren MM pigs after the LPS challenge, which may suggest that those RM pigs responded less detrimentally than MM pigs. Enriched RM pigs showed a higher level of IgM antibodies binding keyhole limpet hemocyanin (KLH) than enriched MM and barren RM pigs, and RM pigs showed a sharper decline in IgG antibodies binding Bovine Serum Albumin (PC-BSA) over time than MM pigs. Hair cortisol concentrations were not affected by enrichment or mixing. To conclude, enrichment did not enhance the speed of recovery from challenges in pigs, although there were indications of reduced stress. Repeated as opposed to single mixing did not seem to aggravate the negative effects of barren housing on resilience and for some parameters even seemed to reduce the negative effects of barren housing.

Unraveling the actual background of second litter syndrome in pigs: based on Large White data.

Second litter syndrome (SLS) in sows is when fertility performance is lower in the second parity than in the first parity. The causes of SLS have been associated with lactation weight loss, premature first insemination, short lactation length, short weaning to insemination interval, season, and farm of farrowing. There is little known about the genetic background of SLS or if it is a real biological problem or just a statistical issue. Thus, we aimed to evaluate risk factors, investigate genetic background of SLS, and estimate the probability of SLS existing due to the statistical properties of the trait. The records of 246 799 litters (total number born, TNB) from 46 218 Large White sows were used. A total of 15 398 sows had SLS. Two traits were defined: first a binominal trait if a sow had SLS or not (biSLS) and second a continuous trait (Range) created by subtracting the total number of piglets born in the first parity (TNB1) from the piglets born in the second parity (TNB2). Lactation length, farm, and season of the farrowing had significant effects on SLS traits when tested as fixed effects in the genetic model. These effects are farm management-related factors. The age at first insemination and weaning to insemination interval were significant only for other reproduction traits (e.g., TNB1, TNB2, litter weight in parity 1 and 2). The heritability of biSLS was 0.05 (on observed scale), whereas heritability of Range was 0.03. To verify the existence of SLS data with records of 50 000 sows and 9 parities was simulated. The simulations showed that the average expected frequency of SLS across all the parities was 0.49 (±0.05) while the observed frequency in the actual data was 0.46 (±0.04). We compared this to SLS frequencies in 67 farms and only 2 farms had more piglets born in the first parity compared to the second. Therefore, on the individual sow level SLS is likely due to statistical properties of the trait, whereas on the farm level SLS is likely due to farm management. Thus, SLS should not be considered an abnormality nor a syndrome if on average the herd litter size in parity 2 is larger than in parity 1.

Investigating pig survival in different production phases using genomic models.

Pig survival is an economically important trait with relevant social welfare implications, thus standing out as an important selection criterion for the current pig farming system. We aimed to estimate (co)variance components for survival in different production phases in a crossbred pig population as well as to investigate the benefit of including genomic information through single-step genomic best linear unbiased prediction (ssGBLUP) on the prediction accuracy of survival traits compared with results from traditional BLUP. Individual survival records on, at most, 64,894 crossbred piglets were evaluated under two multi-trait threshold models. The first model included farrowing, lactation, and combined postweaning survival, whereas the second model included nursery and finishing survival. Direct and maternal breeding values were estimated using BLUP and ssGBLUP methods. Furthermore, prediction accuracy, bias, and dispersion were accessed using the linear regression validation method. Direct heritability estimates for survival in all studied phases were low (from 0.02 to 0.08). Survival in preweaning phases (farrowing and lactation) was controlled by the dam and piglet additive genetic effects, although the maternal side was more important. Postweaning phases (nursery, finishing, and the combination of both) showed the same or higher direct heritabilities compared with preweaning phases. The genetic correlations between survival traits within preweaning and postweaning phases were favorable and strong, but correlations between preweaning and postweaning phases were moderate. The prediction accuracy of survival traits was low, although it increased by including genomic information through ssGBLUP compared with the prediction accuracy from BLUP. Direct and maternal breeding values were similarly accurate with BLUP, but direct breeding values benefited more from genomic information. Overall, a slight increase in bias was observed when genomic information was included, whereas dispersion of breeding values was greatly reduced. Combined postweaning survival presented higher direct heritability than in the preweaning phases and the highest prediction accuracy among all evaluated production phases, therefore standing out as a candidate trait for improving survival. Survival is a complex trait with low heritability; however, important genetic gains can still be obtained, especially under a genomic prediction framework.