Implications

Piglet mortality fuels critical discussions regarding animal welfare concerns. Furthermore, the number of weaned piglets per sow determines the economic success of piglet production. Robustness and a well-performing immune system are a prerequisite for piglet survivability, which is determined by the complex relationships between direct and maternal genetic effects, common litter and management driven environmental effects. This review aims to summarize mechanisms and relationships between immunity, robustness and piglet vitality.

Immune system

The immune system is a highly interactive system composed of integrated, genetically and environmentally regulated sets of cells and molecules. Classically, immunity itself is separated in two pillars, innate and adaptive host defence mechanisms (Tizard, Reference Tizard2013).

The innate immune response is the first line of defence and provides an effective protection. This system is involved in first detection, recognition, killing and delivery of antigens to the next lymphoid tissue and enables the pig to respond rapidly to an infectious agent (Chase and Lunney, Reference Chase and Lunney2012). It consists of physical barriers, phagocytic cells and the production of various mediators with the task to protect, recruit cells through an inflammatory process and activate the adaptive immune system (Tizard, Reference Tizard2013). However, these defence mechanisms are not antigen -specific (Chase and Lunney, Reference Chase and Lunney2012).

The adaptive immune system is antigen-specific. It consists of an immunological memory and takes about 2 to 3 weeks to operate properly after birth and antigen exposure. Mounting an immune response takes longer at first antigen exposure compared to the following encounters with the same antigen. This can result in protection (e.g. vaccination) even if there is no prevailing burden by antigens (Chase and Lunney, Reference Chase and Lunney2012).

Immunocompetence

The immunocompetence of a host is determined by the sum of tolerance and resistance (Rauw, Reference Rauw2012). In livestock, tolerance is described as the ability of an individual to limit the impact of a given pathogen burden on performance (Mulder and Rashidi, Reference Mulder and Rashidi2017). Resistance, however, is characterized by the ability of an individual to reduce the probability of infection or growth of the pathogen by limiting the pathogen burden within itself (Hermesch, Reference Hermesch2014). Based on the definition by Knap (Reference Knap2005), robustness was defined by Colditz and Hine (Reference Colditz and Hine2016), as the consistency of the phenotype of an animal independent of the persistent characteristics of the environment it is kept in. Resilience, however, was defined as the ‘capacity of the animal to return rapidly to its pre-challenge state following short-term exposure to a challenging situation’ (Colditz and Hine, Reference Colditz and Hine2016).

Tolerance and resistance can be abstracted mathematically using reaction norm models (e.g. Raberg et al., Reference Raberg, Graham and Read2009) describing the dynamics of these traits regarding host health and infection intensity (Rauw, Reference Rauw2012). The gap between promising genotypes and their effective performance due to an insufficient provision of resources can be described as unfavourable G×E interactions (Knap, Reference Knap2005). Thereby, reaction norm models quantify G×E interactions by ranking the sensitivity of an individual towards its environment. Tolerance is defined by Simms (Reference Simms2000) as the regression of the relationship between fitness and infection intensity or by Raberg et al. (Reference Raberg, Graham and Read2009) as ‘the rate of change in fitness as parasite burden increases’. Resistance is typically defined as the amount of pathogens in a host or as the inverse of infection intensity (Raberg et al., Reference Raberg, Graham and Read2009).

Generally, tolerance, resistance and resilience are characterized by the need for (re)allocation of resources (Rauw, Reference Rauw2012). According to the allocation theory, an individual possesses a set of resources which are limited and have to be invested amongst the systemic functional areas (Friggens et al., Reference Friggens, Blanc, Berry and Puillet2017). These include growth, metabolism, reproduction, maintenance, retention of energy and nutrition for future use. In this zero-sum system, each unit of resource is only directed to one function, resulting in trade-offs between these systemic functions (Rauw, Reference Rauw2012; Friggens et al., Reference Friggens, Blanc, Berry and Puillet2017). If an immune response is activated, the transformation rate of energy and nutrients is expected to be considerably increased. These resources are then needed and allocated to the immune system; conversely, these mechanisms also work vice versa (Guy et al., Reference Guy, Thomson and Hermesch2012; Rauw, Reference Rauw2012). If an individual passes through life conditions and phases (e.g. extensive growth, reproduction), nutrients and energy are allocated to those somatic functions and immune responses are decreased due to limited physiological resources (Rauw, Reference Rauw2012). It cannot be totally dismissed, that in the situation of a specific immune reaction, deficiencies in, for example, growth and reproduction performance appear. These ‘costs’ for the organism are determined by the environment, the availability of needed resources, and the host’s genotype; however, they cannot be assessed completely (Colditz, Reference Colditz2009).

Piglet vitality and survival

Piglet vitality is the ‘ability of a piglet to survive based on its survival at birth and till weaning’ (Merks et al., Reference Merks, Mathur and Knol2012). Vitality and survival traits are influenced by additive genetic (e.g. behaviour, vigour, immunity), maternal genetic (e.g. behaviour, milk quality and quantity, uterus quality) (Figure 1), common litter (e.g. litter size) and various environmental effects (e.g. temperature, stress and difficulties during farrowing, help with colostrum intake) which are difficult to disentangle mathematically (Knol, Reference Knol2001; Roehe et al., Reference Roehe, Shrestha, Mekkawy, Baxter, Knap, Smurthwaite, Jarvis, Lawrence and Edwards2010).

Figure 1 The connection between piglet survival and immunity. This figure captures the questions and knowledge gaps behind the relationships of the immunocompetence and piglet survival described in this review. Piglet survival is considered within the timeframe between conception and weaning. Thereby, direct genetic and maternal genetic effects influence survivability. The relationship between piglet survivability and immunity and their genetic factors are rarely investigated. However, it is clear that a functioning immune system is a necessary prerequisite for the new-born to survive (modified according to Roehe et al., Reference Roehe, Shrestha and Mekkawy2009).

In Germany, the current piglet pre-weaning mortality rate is 14.87% (erzeugerring.info, 2018). The proportion of pre-weaning losses, however, remained stable, whereas the NBA kept increasing (erzeugerring.info, 2018). This development confirms that breeding for important production traits and larger litters resulted in higher amounts of piglet losses caused by an increased risk for less developed piglets and low individual birth weights (e.g. Edwards, Reference Edwards2002; Grandinson et al., Reference Grandinson, Lund, Rydhmer and Strandberg2002; Alonso-Spilsbury et al., Reference Alonso-Spilsbury, Ramirez-Necoechea, Gonzalez-Lozano, Mota-Rojas and Trujillo-Ortega2007; Hellbrügge et al., Reference Hellbrügge, Tölle, Bennewitz, Henze, Presuhn and Krieter2008; Fix, Reference Fix2010; Baxter et al., Reference Baxter, Rutherford, D’Eath, Arnott, Turner, Sandøe, Moustsen, Thorup, Edwards and Lawrence2013; Rutherford et al., Reference Rutherford, Baxter, D’Eath, Turner, Arnott, Roehe, Ask, Sandoe, Moustsen, Thorup, Edwards, Berg and Lawrence2013). The rivalry in large litters starts in utero, resulting in within- litter variation of birth weights (Rutherford et al., Reference Rutherford, Baxter, D’Eath, Turner, Arnott, Roehe, Ask, Sandoe, Moustsen, Thorup, Edwards, Berg and Lawrence2013) and continues post -farrowing if the number of piglets born exceeds the number of functional teats on the sow (Rootwelt et al., Reference Rootwelt, Reksen, Farstad and Framstad2013).

The main causes for piglet losses are stillbirth, crushing by the sow and starvation and can still be consistently found in literature (Dyck and Swiersta, Reference Dyck and Swiersta1987; Edwards, Reference Edwards2002; Edwards and Baxter, Reference Edwards and Baxter2015). However, these causes were discussed to be effectively the result of low vitality and therefore part of a cascade initiated by poor vigour on the one hand (Edwards and Baxter, Reference Edwards and Baxter2015) and missing mothering abilities on the other (Grandinson et al., Reference Grandinson, Lund, Rydhmer and Strandberg2002). Dyck and Swiersta (Reference Dyck and Swiersta1987) concluded that the main cause for a piglet loss is inadequate colostrum and milk intake in the 1^st days of life. The complex interactions between genetic prerequisites and the environment make it difficult to determine a single reason or rather the real cause for a loss between conception and weaning (Edwards, Reference Edwards2002; Grandinson et al., Reference Grandinson, Lund, Rydhmer and Strandberg2002).

Birth weight was described to be the main factor influencing piglet survival (Roehe and Kalm, Reference Roehe and Kalm2000) and to be a suitable substitute trait to breed for increased piglet survivability due to its higher heritability (Grandinson et al., Reference Grandinson, Lund, Rydhmer and Strandberg2002; Roehe et al., Reference Roehe, Shrestha, Mekkawy, Baxter, Knap, Smurthwaite, Jarvis, Lawrence and Edwards2010). The increase in litter size did not only enhance the risk of lower individual birth weight, but also for a decreased uniformity of birth weights within litters (e.g. Knol, Reference Knol2001). Piglets with a low birth weight and viability at birth show a slower growth and compromised carcass quality (Knol, Reference Knol2001; Fix, Reference Fix2010). However, breeding for higher birth weights does not solve the problem single-handedly (Knol, Reference Knol2001). Heavy piglets prolong the farrowing process for themselves as well as for the following littermates resulting in an increased risk of asphyxia (Grandinson et al., Reference Grandinson, Lund, Rydhmer and Strandberg2002; Trujillo-Ortega et al., Reference Trujillo-Ortega, Mota-Rojas, Olmos-Hernández, Alonso-Spilsbury, González, Orozco, Ramírez-Necoechea and Nava-Ocampo2007). This non-linear relationship between birth weight and stillbirth was also described by, for example, Roehe and Kalm (Reference Roehe and Kalm2000).

Baxter et al. (Reference Baxter, Jarvis, D’Eath, Ross, Robson, Farish, Nevison, Lawrence and Edwards2008) found stillborn piglets were disproportionately long and thin compared to their live born littermates. The authors concluded that not only the body mass index but also the ponderal index (PI) would be reasonable indicators of piglet loss. Fay et al. (Reference Fay, Dey, Saadie, Buhl and Gebski1991) studied human infants and found that the PI is a more reliable indicator for intrauterine growth problems than the birth weight. The PI additionally includes the cubed crown-to-rump length of the piglet (Baxter et al., Reference Baxter, Jarvis, D’Eath, Ross, Robson, Farish, Nevison, Lawrence and Edwards2008) and reflects the change in relative weight for length during gestation (Gluckman and Hanson, Reference Gluckman and Hanson2005). van der Lende and de Jager (Reference van der Lende and de Jager1991) and Rootwelt et al. (Reference Rootwelt, Reksen, Farstad and Framstad2013) showed that a threshold of 1 kg for postpartum survival is needed. Piglets with a birth weight lower than 1 kg have an increased mortality risk, independent of their status in the within-litter variation in birth weight (van der Lende and de Jager, Reference van der Lende and de Jager1991). Low birth weight piglets are less vital, with decreased colostrum intake, a lack of immunoglobulins and a higher risk of pre-weaning mortality due to missing energy reserves, causing hypothermia, crushing and starvation-related deaths (Edwards, Reference Edwards2002). Their resilience to disease, development and future weight gain is decreased whilst the impact of postnatal environmental factors is increased (Edwards, Reference Edwards2002; Le Dividich et al., Reference Le Dividich, Rooke and Herpin2005; Fix, Reference Fix2010).

Relationship between immunity and piglet survival

The primary immune response of the piglet needs 7 to 10 days to develop (Chase and Lunney, Reference Chase and Lunney2012). It is well known that piglet survivability and performance of the immune system are associated via colostrum intake. Newborn piglets are characterized by a lack of immunoglobulins, due to the missing antibody supply from the placenta (Chase and Lunney, Reference Chase and Lunney2012) and missing energy reserves (Theil et al., Reference Theil, Lauridsen and Quesnel2014). Piglets are immediately exposed to microorganisms and pathogens, resulting in a complex microbial flora on its surfaces and in its gastrointestinal tract within hours postpartum. The intestinal microflora is crucial for the development of the immune system. Antibodies are concentrated in the colostrum in the last days of gestation and transferred intact via the gut of the piglet. The intestinal absorption of immunoglobulins from colostrum decreases after 1 to 4 days postpartum. Generally, the concentration of colostrum components changes substantially and rapidly after birth (Theil et al., Reference Theil, Lauridsen and Quesnel2014). The provision of colostrum is crucial for the piglet’s survival, its thermoregulation and growth after birth (Le Dividich et al., Reference Le Dividich, Rooke and Herpin2005). Reasons for reduced colostrum intake lie, for example, in the vitality of the piglet, the competition at the udder and the quantity of colostrum produced by the sow (Tizard, Reference Tizard2013). Le Dividich et al. (Reference Le Dividich, Charneca and Thomas2017) showed that the level of passive immunity acquired through colostrum determines the level of systemic immunity at weaning. Further, they found that piglets with a lower birth weight who survived, needed more colostrum than their heavier littermates. The colostrum production of the sow was independent of litter size and weight. Generally, the birth order was not associated with colostrum intake but with lower immunoglobulin G concentrations in piglets that were born later (Le Dividich et al., Reference Le Dividich, Charneca and Thomas2017).

Genetic aspects of piglet survival and immunity

Immunity

Phenotypes representing the immune system usually include subtypes of leukocytes, as well as T/B lymphocytes (Mangino et al., Reference Mangino, Roederer, Beddall, Nestle and Spector2017). To select pigs for improved health, suitable traits have to be heritable and preferably associated with enhanced performance (Clapperton et al., Reference Clapperton, Glass and Bishop2008). The homeostatic control of the various cell types within the immune system are under genetic and environmental control to a varying extent (Mangino et al., Reference Mangino, Roederer, Beddall, Nestle and Spector2017). Mangino et al. (Reference Mangino, Roederer, Beddall, Nestle and Spector2017) estimated variance components and heritabilities (h ²) in human twins and found that adaptive immune traits are more influenced by genetics, whereas innate immune traits underlie a higher environmental influence.

Table 1 shows a reasonable genetic foundation for most immune parameters from quantitative genetic studies in pigs. Estimations of h ² are highly variable between the studies. These different results could be caused by the number of animals (~200 to 4000), breed and line analysed (Clapperton et al., Reference Clapperton, Bishop and Glass2005) as well as the age or life phase of the animals phenotyped. The fact that challenge studies were conducted (on-farm health status, vaccination reactions, targeted infection) could cause differences in h ². Furthermore, the statistical models used as well as the fixed effects considered (e.g. weight, age, farm, breed) influence h ² estimations. These characteristics make it difficult to compare the findings due to diverse study approaches. For a meaningful estimation of h ² and genetic correlations (r _g), large numbers of phenotyped animals are needed. However, this prerequisite is difficult to realize because taking blood samples is time consuming and the analysis relatively expensive. Furthermore, the impact of the immune system of the sow on the colostrum supply for the piglets and the development of the respective piglets remains uncertain.

Table 1 Heritabilities (h²±SEM) in blood parameters of the porcine immune system (full table in Supplementary Material (Supplementary Table S3))

The relationships between the innate and adaptive immune response were estimated by Flori et al. (Reference Flori, Gao, Laloë, Lemonnier, Leplat, Teillaud, Cossalter, Laffitte, Pinton, Vaureix, de, Bouffaud, Mercat, Lefèvre, Oswald, Bidanel and Rogel-Gaillard2011) and demonstrated the complementarity of innate and adaptive immunity. However, the analyses did not provide any clusters of immune parameters or significant correlations between cell subsets (Flori et al., Reference Flori, Gao, Laloë, Lemonnier, Leplat, Teillaud, Cossalter, Laffitte, Pinton, Vaureix, de, Bouffaud, Mercat, Lefèvre, Oswald, Bidanel and Rogel-Gaillard2011). The relationships between innate and adaptive immunity were described by Seutter (Reference Seutter1995) with the help of the haematological traits neutrophil and lymphocyte concentration. Neutrophil concentrations are expected to have an antagonistic relationship to lymphocyte concentrations, because of the activation of the adaptive immune response (Tizard, Reference Tizard2013). However, this relationship can also be determined by the challenges or the state of development the pig is experiencing. Seutter (Reference Seutter1995) described that sows show a neutrophil dominated blood count after farrowing due to the physical strain of birth. In contrast, piglets express a blood count dominated by lymphocytes indicating that their immune system is responding to their new environment.

To our knowledge, only Clapperton et al. (Reference Clapperton, Glass and Bishop2008 and Reference Clapperton, Diack, Matika, Glass, Gladney, Mellencamp, Hoste and Bishop2009) investigated the relationships between immune parameters and growth performance. The authors found negative correlations between some of the investigated leukocyte blood cells and daily gain and also estimated negative genetic correlations between CD11R1⁺ cells and average daily gain under lower health status. Against this background, we can postulate that a major knowledge gap exists about the genetic impact of the porcine immune system, especially with regards to performance traits and piglet survivability. Furthermore, no studies were conducted to investigate the complex interactions between the dam and her litter or maternal genetic effects (Figure 1). The immune system of the dam could affect phenotypes expressing maternal genetic effects like colostrum quality and quantity as well as uterus and birth conditions. This, however, would influence the ability of the piglet to survive pre- and post-farrowing. The maternal effects are possibly decreasing with time, whilst the challenges for the direct genetic effects are increasing until weaning. Besides, the immune system of the piglet affects phenotypes such as vitality, robustness as well as growth and therefore the overall survivability of the piglet. In summary, there is a lack of knowledge about how the various parts of the immune system influence the genetic potential of the piglet to survive and the ability of the sow to rear her litter.

Piglet survival

Piglet survival can be recorded as survival at farrowing as well as pre-weaning survival at the piglet or sow level (Roehe and Kalm, Reference Roehe and Kalm2000; Hellbrügge et al., Reference Hellbrügge, Tölle, Bennewitz, Henze, Presuhn and Krieter2008). The individual birth weight or weight traits at the litter level were discussed to be suitable substitution traits. At the piglet level, direct genetic effects can be described as the genetic potential of piglet survival (Roehe et al., Reference Roehe, Shrestha and Mekkawy2009). As mentioned above, the genetic capability of the dam to rear piglets is included in the maternal genetic effects (Knol et al., Reference Knol, Leenhouwers and van der Lende2002; Roehe et al., Reference Roehe, Shrestha and Mekkawy2009).

Quantitative genetic studies of piglet survival traits (Table 2) at the sow or piglet level showed mostly low h ² and considerable environmental influence (e.g. farm management). Heritabilities for the individual birth weight are usually marginally higher at the piglet level. Maternal genetic effects are of a similar magnitude as h ² for piglet survival traits and higher for individual birth weight. Traits like mean birth weight per litter showed moderate h ².

Table 2 Heritabilities (h²±SEM) for survival traits in pigs (dam lines and crossbreds) (full table in Supplementary Material (Supplementary Table S4))

h _t ²=total heritability; h _d ²=direct heritability; h _m ²=maternal heritability.

¹ Damgaard et al. (Reference Damgaard, Rydhmer, Lovendahl and Grandinson2003).

² Canario et al. (Reference Canario, Cantoni, Le Bihan, Caritez, Billon, Bidanel and Foulley2006).

³ Hellbrügge et al. (Reference Hellbrügge, Tölle, Bennewitz, Henze, Presuhn and Krieter2008).

⁴ Arango et al. (Reference Arango, Misztal, Tsuruta, Culbertson, Holl and Herring2006) (^4aModel 3, ^4bModel 1).

⁵ Kapell et al. (Reference Kapell, Ashworth, Knap and Roehe2011).

⁶ Roehe et al. (Reference Roehe, Shrestha, Mekkawy, Baxter, Knap, Smurthwaite, Jarvis, Lawrence and Edwards2010).

Genetic correlations between individual survival traits and individual birth weights showed contradictory results. Various studies found negative correlations, indicating that low birth weight is associated with higher numbers of stillborn piglets (e.g. Arango et al., Reference Arango, Misztal, Tsuruta, Culbertson, Holl and Herring2006; Roehe et al., Reference Roehe, Shrestha, Mekkawy, Baxter, Knap, Smurthwaite, Jarvis, Lawrence and Edwards2010). However, Grandinson et al. (Reference Grandinson, Lund, Rydhmer and Strandberg2002) found a positive r _g. Canario et al. (Reference Canario, Cantoni, Le Bihan, Caritez, Billon, Bidanel and Foulley2006) as well as Mulder et al. (Reference Mulder, Hill and Knol2015) confirmed the hypothesis that these traits exhibit a quadratic relationship. This indicates that an ideal birth weight exists (Mulder et al., Reference Mulder, Hill and Knol2015). However, the correlation between pre-weaning survival and individual birth weight was distinctly negative whenever studied (e.g. Arango et al., Reference Arango, Misztal, Tsuruta, Culbertson, Holl and Herring2006; Roehe et al., Reference Roehe, Shrestha, Mekkawy, Baxter, Knap, Smurthwaite, Jarvis, Lawrence and Edwards2010). Therefore, piglets with higher individual birth weights have a higher probability of survival until weaning.

At the sow level, larger litters show higher mortality rates before weaning (Damgaard et al., Reference Damgaard, Rydhmer, Lovendahl and Grandinson2003; Hellbrügge et al., Reference Hellbrügge, Tölle, Bennewitz, Henze, Presuhn and Krieter2008). Unfavourable correlations between the mean within-litter birth weight and litter size were found by Kapell et al. (Reference Kapell, Ashworth, Knap and Roehe2011). Damgaard et al. (Reference Damgaard, Rydhmer, Lovendahl and Grandinson2003) and Sell-Kubiak et al. (Reference Sell-Kubiak, Wang, Knol and Mulder2015b) reported that the within-litter variation of birth weights is under genetic control. However, Sell-Kubiak et al. (Reference Sell-Kubiak, Wang, Knol and Mulder2015b) stress that this trait should be included into a selection index to limit the decreasing impact on the individual birth weight when the selection focusses on reduced within-litter variance. In rabbits and mice, Blasco et al. (Reference Blasco, Martínez-Álvaro, García, Ibáñez-Escriche and Argente2017) and Gutiérrez et al. (Reference Gutiérrez, Nieto, Piqueras, Ibáñez and Salgado2006), concluded that although the within-litter trait variation showed low h ², a genetic foundation exists and consequently selection for a reduced phenotypic variability is possible.

The estimation of direct and maternal genetic effects is difficult, because the quantity and quality of recorded phenotypes is limited. Modelling the litter effect (modelled as the id of the dam and parity) often hampers convergence because there is a considerable drop in observations after first parity caused by selection. Generally, the litter effect represents the same influences for the piglets in a litter (e.g. litter size, uniformity). However, imbalances in parity classes bias the estimations of these effects. The application of cross-fostering complicates the genetic evaluation further, due to the uncertainty whether or not the biological dam or the foster dam actually determines breeding values (Jonas and Rydhmer, Reference Jonas and Rydhmer2018).

Quantitative trait loci, linkage studies and candidate genes

The application of single nucleotide polymorphism (SNP) information in genome-wide association studies (GWAS) give important information on quantitative trait loci (QTL), elucidating the genetic background of the traits of interest (Knol et al., Reference Knol, Nielsen and Knap2016). PigQTLdb (Hu et al., Reference Hu, Park and Reecy2016) shows the current state of research of identified QTL. Genome-wide association studies for domestic animals largely focussed on economically important growth and production factors such as fertility, meat quality and susceptibility to specific infections (e.g. Boddicker et al., Reference Boddicker, Waide, Rowland, Lunney, Garrick, Reecy and Dekkers2012; Onteru et al., Reference Onteru, Fan, Du, Garrick, Stalder and Rothschild2012). A search of the recent publications in this field shows that the amount of genomic analyses of immune and robustness traits increased in the last decade (Supplementary Table S1).

Breeding strategies

Pig breeding programmes classically apply selection indexes based on estimated breeding values and the marginal economic value of each trait using multivariate BLUP models (Knap, Reference Knap2014). The use of genotypic information in the form of SNP and applying various statistical methods revolutionized the potential of breeding value information concerning improved reliabilities as well as reduced generation intervals (Knol et al., Reference Knol, Nielsen and Knap2016). The superiority of applying genotypic information into pig breeding programmes (genomic BLUP) has also been reported (e.g. Guo et al., Reference Guo, Christensen, Ostersen, Wang, Lund and Su2015).

Selection of robust individuals is important because animal welfare concerns can be reduced, whereas the profitability of pig production is increased. The potential implementation of immune and piglet survival traits in a breeding goal for improved robustness is of particular interest and performance tests for selection candidates have to be conceptualized, accordingly. However, various authors (e.g. Onteru et al., Reference Onteru, Fan, Du, Garrick, Stalder and Rothschild2012; Schneider et al., Reference Schneider, Rempel, Snelling, Wiedmann, Nonneman and Rohrer2012; Guo et al., Reference Guo, Su, Christensen, Janss and Lund2016) stress the importance of substantial reference populations to estimate genomic breeding values and the importance of clean phenotyping of the traits of interest.

Breeding for piglet survival was applied in several breeding programmes using different approaches in northern Europe. However, most breeding strategies focussed on the inclusion of litter traits and not individual piglet survival. In Denmark, for example, the trait LS5 was introduced (Nielsen et al., Reference Nielsen, Su, Lund and Madsen2013). Norwegian and Swedish pig breeders included the NBA and the litter weight at week 3 (Rydhmer, Reference Rydhmer2005). In the Netherlands, however, it was discussed to tackle this trait complex by including individual piglet survival into the selection index even though it has a low h ² (Knol et al., Reference Knol, Leenhouwers and van der Lende2002). The advantages of selecting for higher birth weights were regarded critically (Knol et al., Reference Knol, Leenhouwers and van der Lende2002). Roehe et al. (Reference Roehe, Shrestha and Mekkawy2009 and Reference Roehe, Shrestha, Mekkawy, Baxter, Knap, Smurthwaite, Jarvis, Lawrence and Edwards2010) investigated genetic parameters for survival traits in a crossbreeding experiment under outdoor conditions. Sires were selected according to their direct and maternal genetic effects on postnatal piglet survival and a considerable potential to improve individual piglet survival was found. Sell-Kubiak et al. (Reference Sell-Kubiak, Wang, Knol and Mulder2015b) reported promising results for selecting for reduced within-litter variation of birth weights using pedigree and genomic information. Although, phenotypes for piglet survival are labour intensive to record, it has to be recognized that these traits have a high value, especially for breeding organizations (Knap, Reference Knap2014).

Piglets require a well-performing innate immune response directly after birth and sufficient colostrum supply is crucial, especially for weak and small piglets directly after birth. The piglet has no energy resources or adaptive immunity after farrowing. Hence, the quality of the dam’s immune system and its influence on the immunity of the respective offspring are of particular interest (Collins, Reference Collins2014). Especially, the crucial immune reactions for survivability and robustness have to be studied and specified, preferably under different environments. Furthermore, the question if the colostrum quality and production of the sow or the vitality of the piglet is primarily responsible for an increased colostrum intake must be answered. Important traits of the sow like teat number, farrowing behaviour and mothering abilities should be considered in a selection index as well, especially if the focus in the breeding goal lies on litter size (Rydhmer, Reference Rydhmer2000).

Immunocompetence, characterized by specific immune parameters, has not been included in any selection index or breeding value yet. Selection for health traits is mainly concentrated on conformation scores and/or specific disease resistances (e.g. Escherichia coli) (Rydhmer, Reference Rydhmer2005). As described above, limited studies exist on determining the genetic variability of immune traits and the genomic background of the key players in immunity. It is difficult to determine one or two immune parameters to be reasonable traits for incorporation into a breeding programme for improved robustness and survivability.

Challenge studies helped to improve pre-weaning survival in the offspring of boars, which were selected for higher cell-mediated immune response post-vaccination (Harper et al., Reference Harper, Bunter, C Hine, Hermesch and M Collins2018). Mallard et al. (Reference Mallard, Wilkie, Kennedy and Quinton1992) selected pigs with high and low immune response to study the performance and immune response of the animals post challenge (e.g. Magnusson et al., Reference Magnusson, Wilkie, Mallard, Rosendal and Kennedy1998; Wilkie and Mallard, Reference Wilkie and Mallard1999). Stear et al. (Reference Stear, Bishop, Mallard and Raadsma2001) concluded that breeding for a specific immune response does result in higher susceptibility for other diseases.

Promising genetic resistance against the porcine reproductive and respiratory syndrome (PRRS) was reviewed by Reiner (Reference Reiner2016) and Dekkers et al. (Reference Dekkers, Rowland, Lunney and Plastow2017). However, Dekkers et al. (Reference Dekkers, Rowland, Lunney and Plastow2017) stress that due to the variability of PRRS a resistance is not feasible, but a reduced susceptibility is. Furthermore, the need for a closer inspection of the complete function of potential candidate genes (e.g. receptors) was emphasized by Reiner (Reference Reiner2016). This was confirmed by Popescu et al. (Reference Popescu, Gaudreault, Whitworth, Murgia, Nietfeld, Mileham, Samuel, Wells, Prather and Rowland2017) who reported that genetically edited pigs lacking the virus receptor CD163 for African swine fever died post virus infection.

In order to characterize and breed for immunocompetence, specific immune responses towards challenges are not suitable as a basis for selection decisions. Otherwise, selection for a specific immune response cannot be calibrated without challenging the pigs immune system (Hermesch, Reference Hermesch2014). Hence, what is crucially missing is the identification of traits or trait complexes to breed for improved immunity.

Breeding goals for immunocompetence and health traits changed in their specificity (tolerance, resistance, robustness and resilience), definitions, context and requirements over the last two decades (Kanis et al., Reference Kanis, van den Belt, Groen, Schakel and Greef2004; Hermesch, Reference Hermesch2014). Robust pigs should achieve high performance under all possible and even in non-optimized housing conditions and challenge situations (Knap, Reference Knap2005). Accordingly, Knap (Reference Knap2009) defined sustainable breeding and increasing robustness as selection for animals combining a high production potential with resilience to external stressors (psychological, physical or microbial). Studies on resilience focussed on immunity, performance (Wilkie and Mallard, Reference Wilkie and Mallard1999; Mulder and Rashidi, Reference Mulder and Rashidi2017), animal behaviour (Kanis et al., Reference Kanis, van den Belt, Groen, Schakel and Greef2004) and stress reactions on endocrinological levels (e.g. Mormede and Terenina, Reference Mormede and Terenina2012). In this context, the increased uniformity of livestock as well as G×E interactions (Mulder, Reference Mulder2016) are often discussed with the help of conceptual frameworks (e.g. the thermoregulation model in Kanis et al., Reference Kanis, van den Belt, Groen, Schakel and Greef2004) to discuss if the traits of interest can be translated into an applicable breeding goal (Hermesch, Reference Hermesch2014).

Nevertheless, breeding for disease resistance can be seen critically. If resistance towards specific pathogens and viruses is established, the question arises whether or not this leads to breeding animals less flexible to different environmental conditions. Guy et al. (Reference Guy, Thomson and Hermesch2012) and Flori et al. (Reference Flori, Gao, Laloë, Lemonnier, Leplat, Teillaud, Cossalter, Laffitte, Pinton, Vaureix, de, Bouffaud, Mercat, Lefèvre, Oswald, Bidanel and Rogel-Gaillard2011) discussed that selection for response to a specific pathogen may result in unpredictable responses to other pathogens. Therefore, Guy et al. (Reference Guy, Thomson and Hermesch2012) recommend a careful evaluation of selection traits and criteria with regards to their consequences, before their incorporation into a breeding programme. Mulder et al. (Reference Mulder, Hill and Knol2015) described trade-offs between the flexibility of an animal to react to various environmental challenges on the one hand, and a lowered plasticity, resulting in high performance, on the other. This was already shown by a higher prevalence of reproductive and health-related problems in livestock under non-optimized production premises (Knap and Su, Reference Knap and Su2008). Therefore, breeding for tolerance would be more beneficial to increasing robustness if it increases the genetic variability of pigs to react to environmental challenges without harming the limited variability of pig performance accepted by the following actors of the value chain.

Concerning the improvement of piglet survivability, the role of immunocompetence needs to be further investigated. Whether the immune reaction must be high or low to be vital and resilient is not defined yet. It is not clear if an optimized immune response is a substitute for piglet survival or could be included into a selection index for improved survivability. Moreover, the economic value of immunocompetence is intricate to evaluate.