Genetic analysis of pig survival up to commercial weight in a crossbred population

Review: Improving pig survival with a focus on birthweight: a practical breeding perspective

Survival of growing pigs through to slaughter age is not only a key driver of profitability but also has implications for animal welfare. Changing preweaning mortality by over 3% gives a similar change in profit per pig as changing postweaning mortality by 1%. There is significant scope to improve both traits through management and breeding to improve survival. The aim of this literature review was to explore the relationship between litter size and piglet birthweight and the detrimental impact this negative association has had on pig survival, along with genetic strategies that have been implemented in breeding programmes. It is suggested that the primary effect of litter size on mortality was indirect, through the effects of litter size on individual piglet birthweights. The circumstances affecting the litter a piglet was born into were the most important for determining the birthweight of individual piglets, rather than the genetic make-up of the individual piglet itself. Therefore, breeding programmes should include the average piglet birthweight of a litter (i.e., a sow trait) rather than individual piglet birthweight to maintain the weight of piglets at birth. The relative weighting of litter size and average piglet birthweight should be done in a manner that avoids selecting heavy pigs from small litters. Additional genetic strategies to improve survival include survival at the litter level, or survival of individual piglets or enhanced through the use of genomic information. At the litter level, litter size at day 5 and weaning can be considered as sow traits, but the use of these traits depends on the recording environment. At the individual piglet level, pre- and postweaning survival can be recorded as 0/1 traits and analysed directly. Although heritabilities are low for all these traits, genetic improvements can be made. For preweaning survival, the genes of the nurse sow are more important than the genes of the individual piglet. The nurse sow model captures both the lactation and gestation effects, and the information obtained when piglets born from different litters are reared together. However, once a piglet is weaned, its own genes became more important for the expression of postweaning mortality outcomes. Finally, for a successful selection programme, combining the average piglet birthweight at the litter level and mortality data based on individual piglet records (not solely birthweight) might yield the best response in piglet survival.

Genetic variation in piglet mortality in outdoor organic production systems

Piglet mortality from farrowing to weaning is a major concern, especially in outdoor organic production systems. This issue might impair animal welfare and generate economic losses for the farmer. In particular, it is difficult to apply management tools that are commonly used for indoor pig production systems to organic or outdoor production systems. Genetics and breeding approaches might be used to improve piglet survival. However, knowledge remains limited on the genetic background underlying survival traits in organic pigs that are born and reared outdoors. Here, we investigated the mortality of piglets from farrowing to weaning in an outdoor organic pig population and suggested genetic strategies to reduce piglet mortality in this production system. The experiment included mortality records of piglets from farrowing to weaning (around 69 days of age). Pedigree-based threshold models were used to analyse the mortality traits of piglets at 0-3 days of age, 4-11 days, and 12 days to weaning. Stillborn piglets were included in the group of piglets that died at 0-3 days of age. We found that the mortality rate from farrowing to weaning was, on average, 19.2%. However, most piglet deaths (79.1%) occurred at 0-11 days of age. As the age of piglets increased, the direct heritability of piglet mortality rose from 0 to 0.04, whereas maternal heritability decreased from 0.03 to a non-significant value. Piglets with higher BW had a lower mortality rate. However, the genetic correlations between maternal effects on piglet mortality and piglet BW were not significant; thus, selection for piglets with higher BW at around 10 days of age, through improving maternal genetics, would not reduce piglet mortality. Piglet mortality increased from sows with increasing number of parities. Crossbreeding also reduced piglet mortality. In conclusion, selection focusing on sow genotype, the use of younger sows, and crossbreeding could contribute to maintain piglet mortality at lower levels in outdoor organic pig production systems.

Genetic parameters of drinking and feeding traits of wean-to-finish pigs under a polymicrobial natural disease challenge

Background

The pork industry faces unprecedented challenges from disease, which increases cost of production and use of antibiotics, and reduces production efficiency, carcass quality, and animal wellbeing. One solution is to improve the overall resilience of pigs to a broad array of common diseases through genetic selection. Behavioral changes in feeding and drinking are usually the very first clinical signs when animals are exposed to stressors such as disease. Changes in feeding and drinking behaviors in diseased pigs may reflect the way they cope with the challenge and, thus, could be used as indicator traits to select for disease resilience. The objectives of this study were to estimate genetic parameters of feeding and drinking traits for wean-to-finish pigs in a natural polymicrobial disease challenge model, to estimate genetic correlations of feeding and drinking traits with growth rate and clinical disease traits, and to develop indicator traits to select for disease resilience.

Results

In general, drinking traits had moderate to high estimates of heritability, especially average daily water dispensed, duration, and number of visits (0.44 to 0.58). Similar estimates were observed for corresponding feeding traits (0.35 to 0.51). Most genetic correlation estimates among drinking traits were moderate to high (0.30 to 0.92) and higher than among feeding traits (0 to 0.11). Compared to other drinking traits, water intake duration and number of visits had relatively stronger negative genetic correlation estimates with treatment rate and mortality, especially across the challenge nursery and finisher (− 0.39 and − 0.45 for treatment rate; − 0.20 and − 0.19 for mortality).

Conclusion

Most of the recorded drinking and feeding traits under a severe disease challenge had moderate to high estimates of heritability, especially for feed or water intake duration and number of visits. Phenotypic and genetic correlations among the recorded feeding traits under disease were generally low but drinking traits showed high correlations with each other. Water intake duration and number of visits are potential indicator traits to select for disease resilience because of their high heritability and had moderate genetic correlations with treatment and mortality rates under severe disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40104-021-00622-x.

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.

Impact of including the cause of missing records on genetic evaluations for growth in commercial pigs

It is of interest to evaluate crossbred pigs for hot carcass weight (HCW) and birth weight (BW); however, obtaining a HCW record is dependent on livability (LIV) and retained tag (RT). The purpose of this study is to analyze how HCW evaluations are affected when herd removal and missing identification are included in the model and examine if accounting for the reasons for missing traits improves the accuracy of predicting breeding values. Pedigree information was available for 1,965,077 purebred and crossbred animals. Records for 503,716 commercial three-way crossbred terminal animals from 2014 to 2019 were provided by Smithfield Premium Genetics. Two pedigree-based models were compared; model 1 (M1) was a threshold-linear model with all four traits (BW, HCW, RT, and LIV), and model 2 (M2) was a linear model including only BW and HCW. The fixed effects used in the model were contemporary group, sex, age at harvest (for HCW only), and dam parity. The random effects included direct additive genetic and random litter effects. Accuracy, dispersion, bias, and Pearson correlations were estimated using the linear regression method. The heritabilities were 0.11, 0.07, 0.02, and 0.04 for BW, HCW, RT, and LIV, respectively, with standard errors less than 0.01. No difference was observed in heritabilities or accuracies for BW and HCW between M1 and M2. Accuracies were 0.33, 0.37, 0.19, and 0.23 for BW, HCW, RT, and LIV, respectively. The genetic correlation between BW and RT was 0.34 ± 0.03, and between BW and LIV was 0.56 ± 0.03. Similarly, the genetic correlation between HCW and RT was 0.26 ± 0.04, and between HCW and LIV was 0.09 ± 0.05, respectively. The positive and moderate genetic correlations between BW and other traits imply a heavier BW resulted in a higher probability of surviving to harvest. Genetic correlations between HCW and other traits were lower due to the large quantity of missing records. Despite the heritable and correlated aspects of RT and LIV, results imply no major differences between M1 and M2; hence, it is unnecessary to include these traits in classical models for BW and HCW.

Vitality in relation to litter size of crossbred pigs and the effect of the terminal sire line

Context Most research on sire lines is linked to growth and carcass traits. Only a limited number of field trials explore the effect of sire line on piglet vitality, litter size and the interactions between these traits. Aim The aim of this study was to examine the effect of sire line on the growth performance and vitality of progeny from birth to weaning and to evaluate the lines with respect to their impact on litter size. Methods Data included 150 litters of a Synthetic sire line (A) and 154 of a Piétrain sire line (B), with 4209 piglets born alive, which resulted from matings to 337 dams (Camborough PIC). The numbers of total born and born alive piglets per litter were recorded. Within 24 h after birth, piglet individual birthweight (BWbirth), sex (male/female) and body temperature (BT) were also recorded. At weaning, mortality rates and weaned pigs per sow were registered. At the day of weaning, 665 randomly chosen pigs were individually weighed. Weaning weights (WW) were used to calculate the weaning average daily gain (WADG). Key results Sire line significantly affected number of total born (P < 0.0001), number born alive (P < 0.01) and number of weaned pigs per sow (P < 0.01). Across lines, each additional piglet per litter resulted in a 31.2 g decline in BWbirth (P < 0.001). Larger litter sizes, higher BWbirth (P < 0.01) and piglets with a lower BT (P < 0.0001) were detected in litters of Sire line B compared with litters of Sire line A. No differences between lines were detected for WADG, WW and pre-weaning mortality (P > 0.05). A positive correlation between birthweight and WW resulted in a correspondingly higher WADG (P < 0.0001). Overall, heavier BWbirth piglets had a higher BT (P < 0.0001). Conclusions The present study indicates that Sire line B would offer a possibility to maintain litter size at a high level and, simultaneously, achieve higher BWbirth, with consequently more vital piglets. Implication It is important to emphasise that further selection for litter size in dam lines is not indicated in terms of animal welfare but also production efficiency. Instead, it seems feasible to follow the above strategy and stabilise litter size at a high level, while at the same time breeding for vitality and survivability in sire lines.

Genetic analysis of disease resilience in wean-to-finish pigs from a natural disease challenge model

The objective was to estimate the genetic parameters of performance and resilience of growing pigs under disease. Data were from 3,139 Yorkshire × Landrace wean-to-finish pigs that were exposed to a natural polymicrobial disease challenge that was established by entering naturally infected animals into a nursery barn, targeting various viral and bacterial diseases. The challenge was maintained by entering batches of 60 or 75 healthy nursery pigs every 3 wk in a continuous flow system. Traits analyzed included average daily gain (ADG), feed intake (ADFI) and duration (ADFD); feed conversion ratio (FCR); residual feed intake (RFI); mortality (MOR); number of health treatments (TRT); health scores (HScore); carcass weight (CWT), back fat (CBF) and loin depth (CLD); dressing percentage (DRS); lean yield (LYLD); day-to-day variation in feed intake and duration (VARFI and VARDUR); and the proportion of off-feed days (OFFFI and OFFDUR). Analyses were performed by mixed linear models with genomic relationships. The resilience traits, such as TRT, MOR, and HScore, were lowly heritable (up to 0.15) but had high genetic correlations with each other. Performance traits, such as ADG, ADFI, ADFD, FCR, RFI, and carcass traits, were moderate to highly heritable (0.17 to 0.49). Heritabilities of resilience indicator traits such as OFF and VAR had low to moderate heritabilities (0.08 to 0.23) but were higher when based on duration vs. amount. ADFI had a low genetic correlation with ADFD (0.13). ADG in the challenge nursery had stronger negative genetic correlations with both TRT and MOR than ADG in the finisher (-0.37 to -0.74 vs. -0.15 to -0.56). ADFI and FCR had moderate negative (-0.21 to -0.39) and positive (0.34 to 0.49) genetic correlations, respectively, with TRT and MOR. ADFD and RFI had very low genetic correlations with TRT and MOR. CWT and DRS were moderately negatively correlated with TRT and MOR (-0.33 to -0.59). Resilience indicator traits based on feed intake or duration had moderate to high positive genetic correlations with TRT (0.18 to 0.81) and MOR (0.33 to 0.87). In conclusion, performance and resilience traits under a polymicrobial disease challenge are heritable and can be changed by selection. Phenotypes extracted from feed intake patterns can be used as genetic indicator traits for disease resilience. Most promising is day-to-day variation in intake duration, which had a sizeable heritability (0.23) and favorable genetic correlations with MOR (0.79) and treatment rate (0.20).

Effects of sire line, birth weight and sex on growth performance and carcass traits of crossbred pigs under standardized environmental conditions

A variety of available terminal sire lines makes the choice of terminal sire line complex for the pig producer. Higher birth weights are important for subsequent growth performance and selection for this trait is also necessary in sire lines. The aim was to investigate the effect of sire line, birth weight and gender on growth performance, carcass traits and meat quality. In total 3844 crossbred pigs from Camborough Pig Improvement Company (PIC) dams matched with either a Synthetic (A) or Piétrain (B) sire line were used. Pigs from line A grew faster (p<0.01), showed higher feed intake (p<0.01) and reached a higher final body weight (p≤0.01), but they had a similar efficiency (p=0.179). Leaner carcasses and heavier primal cuts (p<0.001) were observed in pigs from line B. Carcasses from pigs sired by line A had higher meat quality (p<0.001). Males had a higher growth rate (p≤0.05) but had a poorer feed efficiency (p<0.01). Heavier birth weight pigs and females had leaner, higher value carcasses with heavier primal cuts (p<0.001) compared to middle and low birth weight females or males. Sire line by sex interactions was significant for growth (p≤0.05) and carcass traits (p<0.001). Interaction between sire line and birth weight classes were only detected for loin depth (p<0.01). Line A is preferable if the numbers of fatting pigs per fattening place and year should be improved, and line B is an option to increase leanness and carcass primal cuts.

Postweaning mortality in commercial swine production. I: review of non-infectious contributing factors

Postweaning mortality is a complex causal matrix involving animal, environment, and infectious etiologic factors. Despite advances in swine productivity such as total pigs born, growth rate, feed intake, and efficiency, there have been modest to no improvements in postweaning mortality rates over the last several years. Industry averages for postweaning mortality range from four to eight percent for each the nursery, grow-finish, or wean-finish stages. Retrospective mortality causal analyses of individual databases have been performed. However, little information derived from meta-analysis, systematic review, or comprehensive literature reviews are available. In order to develop and evaluate strategies to comprehensively manage and reduce postweaning mortality, addressing the complexity and range of impact that factors have on mortality is necessary to identify and prioritize such contributing factors. Our objective is to describe the current state of knowledge regarding non-infectious causes of postweaning mortality, focusing on estimates of frequency and magnitude of effect where available. Postweaning mortality can be generalized into non-infectious and infectious causes, with non-infectious factors further classified into anatomic abnormalities, toxicity, animal factors, facility factors, nutritional inadequacies, season, and management factors. Important non-infectious factors that have been identified through review of literature include birth weight, pre-weaning management, weaning age and weight, and season. Additionally, reasons for mortality with a low incidence but a high magnitude include abdominal organ torsion/volvulus, sodium ion or ionophore toxicosis, or dietary imbalance due to feed formulation or manufacture error. Many interactive effects are present between and among infectious and non-infectious factors, but an important trend is the impact that non-infectious factors have on the incidence, severity, and resolution of infectious disease. Strategies to reduce postweaning mortality must consider the dynamic, complex state that forms the causal web. Control of postweaning mortality through understanding of the complexity, evaluation of mortality reduction strategies through rigorous scientific evaluation, and implementation remains an area of opportunity for continued growth and development in the global swine industry.

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

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

Selection for productivity and robustness traits in pigs

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 resilience may be based on performance and immune 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.