Genetic variation for farrowing rate in pigs in response to change in photoperiod and ambient temperature

Reaction-norm animal model analysis of average daily gain heat tolerance in purebred Duroc pigs

The present study aimed to genetically improve growth performance under high-heat environments by specifically designing a reaction-norm animal model (RNAM) for purebred Duroc pigs in Japan. A total of 54,750 records of average daily gain (ADG) measured for pigs reared at four farms in different prefectures were analyzed. Estimated maximum daily temperatures at the respective farm locations were used to calculate the average cumulative thermal load (TL). The TL values served as an indicator of high-heat environments for pigs. The plausible cumulative period length and threshold temperature for calculating TL were determined to be 8 weeks until just before shipping and 25°C, respectively. Variance components were estimated via RNAM analysis using TL as a linear covariate. The estimated additive genetic variances under both responsive and non-responsive to TL were found to be significant. Moreover, the estimated heritability of ADG ranged from 0.38 to 0.73 for TL values of 0-8. These results suggest that the RNAM developed holds the potential for improving the genetic ability of growth under high-heat environments in pigs.

Season and temperature do not affect cumulative live birth rate and time to live birth in in vitro fertilization

Objective

To explore whether season and temperature on oocyte retrieval day affect the cumulative live birth rate and time to live birth.

Methods

This was a retrospective cohort study. A total of 14420 oocyte retrieval cycles from October 2015 to September 2019. According to the date of oocyte retrieval, the patients were divided into four groups (Spring(n=3634);Summer(n=4414); Autumn(n=3706); Winter(n=2666)). The primary outcome measures were cumulative live birth rate and time to live birth. The secondary outcome measures included the number of oocytes retrieved, number of 2PN, number of available embryos and number of high-quality embryos.

Results

The number of oocytes retrieved was similar among the groups. Other outcomes, including the number of 2PN (P=0.02), number of available embryos (p=0.04), and number of high-quality embryos (p<0.01) were different among the groups. The quality of embryos in summer was relatively poor. There were no differences between the four groups in terms of cumulative live birth rate (P=0.17) or time to live birth (P=0.08). After adjusting for confounding factors by binary logistic regression, temperature (P=0.80), season (P=0.47) and duration of sunshine(P=0.46) had no effect on cumulative live births. Only maternal age (P<0.01) and basal FSH (P<0.01) had an effect on cumulative live births. Cox regression analysis suggested no effect of season(P=0.18) and temperature(P=0.89) on time to live birth. Maternal age did have an effect on time to live birth (P<0.01).

Conclusion

Although season has an effect on the embryo, there was no evidence that season or temperature affect the cumulative live birth rate or time to live birth. It is not necessary to select a specific season when preparing for IVF.

Estimation of off-farm temperatures and temperature-humidity index from meteorological observation records

The objective of this study was to devise an optimal method for estimating air temperatures outside pig farms to be able to evaluate the genetic performance of pigs. Using daily temperature data from Japan Meteorological Agency meteorological stations, we investigated the optimal number of observation weather stations (number of records), and methods of estimating outside temperature when temperature records are missing. We also considered the possibility of using relative humidity data. Our results showed that it is possible to use records from the three nearest weather stations to estimate off-farm ambient temperatures. We also concluded that estimates of outside temperatures when records are missing can be made by using data from at least one weather station that holds a full set of data. The correlation coefficients between the true THI (temperature-humidity index) and the estimated THI and the average daily temperature were almost the same, indicating that the daily average temperature can be used instead of estimated THI.

Effect of Dietary Supplementation with Mannose Oligosaccharides on the Body Condition, Lactation Performance and Their Offspring of Heat-Stressed Sows

The aim of this study was to determine the effects of dietary supplementation with mannose oligosaccharide (MOS) on the condition of the body and the reproductive and lactation performances of sows. Eighty pregnant sows were randomly assigned to four groups with a 2 × 2 factorial design: with or without MOS (1 g/kg) and with or without heat stress (HS) challenge. The temperature in the HS groups (HS and HM group) was controlled at 31.56 ± 1.22 °C, while the temperature in the active cooling (AC) groups (AC and AM group) was controlled at 23.49 ± 0.72 °C. The weight loss of sows in the AC group was significantly lower than that of sows in the HS group (p < 0.01). The weight and backfat thickness loss of sows supplemented with MOS displayed a downward trend. The average birth weight of the litter significantly increased in the HM group (basic diet + MOS) compared with the HS group (p < 0.05). The milk protein of sows significantly decreased under the HS condition at 2 and 12 h after delivery (p < 0.05). However, the milk immunoglobin G (IgG) of sows in the HS group increased significantly compared with that of sows in the HM group (p < 0.05) at 12 and 24 h after delivery. The levels of serum urea nitrogen (UREA) and glucose (GLU) decreased significantly under the HS condition (p < 0.05), while the level of interleukin-6 (IL-6) increased significantly under the HS condition (p < 0.05). Dietary supplementation with MOS also significantly reduced TNF-α under the AC conditions (p < 0.05). In conclusion, HS significantly affected the body condition, lactation performances and their offspring of sows. However, dietary supplementation with 1 g/kg MOS did not result in statistically significant changes.

Heritability and genetic correlation estimates of semen production traits with litter traits and pork production traits in purebred Duroc pigs

We estimated heritabilities of semen production traits and their genetic correlations with litter traits and pork production traits in purebred Duroc pigs. Semen production traits were semen volume, sperm concentration, proportion of morphologically normal sperms, total number of sperm, and total number of morphologically normal sperm. Litter traits at farrowing were total number born, number born alive, number stillborn, total litter weight at birth, mean litter weight at birth, and piglet survival rate at birth. Litter traits at weaning were litter size at weaning, total litter weight at weaning, mean litter weight at weaning, and piglet survival rate from birth to weaning. Pork production traits were average daily gain, backfat thickness, and loin muscle area. We analyzed 45,913 semen collection records of 896 boars, 6,950 farrowing performance records of 1,400 sows, 2,237 weaning performance records of 586 sows, and individual growth performance records of 9,550 animals measured at approximately 5 mo of age. Heritabilities were estimated using a single-trait animal model. Genetic correlations were estimated using a 2-trait animal model. Estimated heritabilities of semen production traits ranged from 0.20 for sperm concentration to 0.29 for semen volume and were equal to or higher than those of litter traits, ranging from 0.06 for number stillborn and piglet survival rate at birth to 0.25 for mean litter weight at birth, but lower than those of pork production traits, ranging from 0.50 for average daily gain to 0.63 for backfat thickness. In many cases, the absolute values of estimated genetic correlations between semen production traits and other traits were smaller than 0.3. These estimated genetic parameters provide useful information for establishing a comprehensive pig breeding scheme.

Genetic parameters of 5 semen production traits, 10 litter traits, and 3 pork production traits in purebred Duroc pigs was estimated. Heritabilities of semen production traits ranged from 0.20 for sperm concentration to 0.29 for semen volume and were equal to or higher than those of litter traits, ranging from 0.06 for number stillborn and piglet survival rate at birth to 0.25 for mean litter weight at birth, but lower than those of pork production traits, ranging from 0.50 for average daily gain to 0.63 for backfat thickness. In many cases, the absolute values of genetic correlations between semen production traits and other traits were smaller than 0.3. These estimated genetic parameters provide useful information for establishing a comprehensive pig breeding scheme.

Timing and temperature thresholds of heat stress effects on fertility performance of different parity sows in Spanish herds

High temperature is an environmental factor that impairs sow fertility. In this study, we identified the critical weeks for heat stress effects on aspects of fertility performance, namely weaning-to-first-service interval (WSI) and farrowing rate (FR). We also examined the threshold temperatures above which the fertility performance deteriorated and whether there were any differences between parities regarding heat stress effects or thresholds. Performance data of sows in 142 herds from 2011 to 2016 were matched to appropriate weekly averaged daily maximum temperatures (Tmax) from weather stations close to the herds. Two types of ratios (i.e., ratio for WSI and odds ratio for FR) were used to identify the critical weeks for heat stress by comparing the respective measures for two sow groups based on Tmax in different weeks around weaning or service events. The ratios for WSI were calculated between groups of sows exposed to Tmax ≥ 27 °C or <27 °C in each week before weaning, with the Tmax cutoff value based on a recent review study. Similarly, the odds ratios for FR for the two groups were calculated in weeks around service. The weeks with the largest differences in the fertility measures between the two Tmax groups (i.e., the highest ratio for WSI and the lowest odds ratio for FR) were considered to be the critical weeks for heat stress. Also, piecewise models with different breakpoints were constructed to identify the threshold Tmax in the critical week. The breakpoint in the best-fit model was considered to be the threshold Tmax. The highest ratios for WSI were obtained at 1 to 3 wk before weaning in parity 1 and 2 or higher sow groups. The threshold Tmax leading to prolonged WSI was 17 °C for parity 1 sows and 25 °C for parity 2 or higher sows. Increasing Tmax by 10 °C above these thresholds increased WSI by 0.65, and 0.33 to 0.35 d, respectively (P < 0.01). For FR, the lowest odds ratios were obtained at 2 to 3 wk before service in parity 0, 1, and 2 or higher sow groups. The threshold Tmax leading to reductions in FR was 20, 21, and 24 to 25 °C for parity 0, 1, and 2 or higher sow groups, respectively. Increasing Tmax by 10 °C above these thresholds decreased FR by 3.0%, 4.3%, and 1.9% to 2.8%, respectively (P < 0.01). These results indicate that the critical weeks for heat stress were 2 to 3 wk before service for FR and 1 to 3 wk before weaning for WSI. The decreases in fertility performance in parity 0 to 1 sows started at temperatures 3 to 8 °C lower than in parity 2 or higher sows.

Genotype-by-environment interactions for reproduction, body composition, and growth traits in maternal-line pigs based on single-step genomic reaction norms

BACKGROUND

There is an increasing need to account for genotype-by-environment (G × E) interactions in livestock breeding programs to improve productivity and animal welfare across environmental and management conditions. This is even more relevant for pigs because selection occurs in high-health nucleus farms, while commercial pigs are raised in more challenging environments. In this study, we used single-step homoscedastic and heteroscedastic genomic reaction norm models (RNM) to evaluate G × E interactions in Large White pigs, including 8686 genotyped animals, for reproduction (total number of piglets born, TNB; total number of piglets born alive, NBA; total number of piglets weaned, NW), growth (weaning weight, WW; off-test weight, OW), and body composition (ultrasound muscle depth, MD; ultrasound backfat thickness, BF) traits. Genetic parameter estimation and single-step genome-wide association studies (ssGWAS) were performed for each trait.

RESULTS

The average performance of contemporary groups (CG) was estimated and used as environmental gradient in the reaction norm analyses. We found that the need to consider heterogeneous residual variance in RNM models was trait dependent. Based on estimates of variance components of the RNM slope and of genetic correlations across environmental gradients, G × E interactions clearly existed for TNB and NBA, existed for WW but were of smaller magnitude, and were not detected for NW, OW, MD, and BF. Based on estimates of the genetic variance explained by the markers in sliding genomic windows in ssGWAS, several genomic regions were associated with the RNM slope for TNB, NBA, and WW, indicating specific biological mechanisms underlying environmental sensitivity, and dozens of novel candidate genes were identified. Our results also provided strong evidence that the X chromosome contributed to the intercept and slope of RNM for litter size traits in pigs.

CONCLUSIONS

We provide a comprehensive description of G × E interactions in Large White pigs for economically-relevant traits and identified important genomic regions and candidate genes associated with GxE interactions on several autosomes and the X chromosome. Implementation of these findings will contribute to more accurate genomic estimates of breeding values by considering G × E interactions, in order to genetically improve the environmental robustness of maternal-line pigs.

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).

Genomics of Heat Tolerance in Reproductive Performance Investigated in Four Independent Maternal Lines of Pigs

Improving swine climatic resilience through genomic selection has the potential to minimize welfare issues and increase the industry profitability. The main objective of this study was to investigate the genetic and genomic determinism of tolerance to heat stress in four independent purebred populations of swine. Three female reproductive traits were investigated: total number of piglets born (TNB), number of piglets born alive (NBA) and average birth weight (ABW). More than 80,000 phenotypic and 12,000 genotyped individuals were included in this study. Genomic random-regression models were fitted regressing the phenotypes of interest on a set of 95 environmental covariates extracted from public weather station records. The models yielded estimates of (genomic) reactions norms for individual pigs, as indicator of heat tolerance. Heat tolerance is a heritable trait, although the heritabilities are larger under comfortable than heat-stress conditions (larger than 0.05 vs. 0.02 for TNB; 0.10 vs. 0.05 for NBA; larger than 0.20 vs. 0.10 for ABW). TNB showed the lowest genetic correlation (-38%) between divergent climatic conditions, being the trait with the strongest impact of genotype by environment interaction, while NBA and ABW showed values slightly negative or equal to zero reporting a milder impact of the genotype by environment interaction. After estimating genetic parameters, a genome-wide association study was performed based on the single-step GBLUP method. Heat tolerance was observed to be a highly polygenic trait. Multiple and non-overlapping genomic regions were identified for each trait based on the genomic breeding values for reproductive performance under comfortable or heat stress conditions. Relevant regions were found on chromosomes (SSC) 1, 3, 5, 6, 9, 11, and 12, although there were important regions across all autosomal chromosomes. The genomic region located on SSC9 appears to be of particular interest since it was identified for two traits (TNB and NBA) and in two independent populations. Heat tolerance based on reproductive performance indicators is a heritable trait and genetic progress for heat tolerance can be achieved through genetic or genomic selection. Various genomic regions and candidate genes with important biological functions were identified, which will be of great value for future functional genomic studies.

Optimizing design to estimate genetic correlations between environments with common environmental effects

Breeding programs for different species aim to improve performance by testing members of full-sib (FS) and half-sib (HS) families in different environments. When genotypes respond differently to changes in the environment, this is defined as genotype by environment (G × E) interaction. The presence of common environmental effects within families generates covariance between siblings, and these effects should be taken into account when estimating a genetic correlation. Therefore, an optimal design should be established to accurately estimate the genetic correlation between environments in the presence of common environmental effects. We used stochastic simulation to find the optimal population structure using a combination of FS and HS groups with different levels of common environmental effects. Results show that in a population with a constant population size of 2,000 individuals per environment, ignoring common environmental effects when they are present in the population will lead to an upward bias in the estimated genetic correlation of on average 0.3 when the true genetic correlation is 0.5. When no common environmental effects are present in the population, the lowest standard error (SE) of the estimated genetic correlation was observed with a mating ratio of one dam per sire, and 10 offspring per sire per environment. When common environmental effects are present in the population and are included in the model, the lowest SE is obtained with mating ratios of at least 5 dams per sire and with a minimum number of 10 offspring per sire per environment. We recommend that studies that aim to estimate the magnitude of G × E in pigs, chicken, and fish should acknowledge the potential presence of common environmental effects and adjust the mating ratio accordingly.

Variance estimates are similar using pedigree or genomic relationships with or without the use of metafounders or the algorithm for proven and young animals1

With an increase in the number of animals genotyped there has been a shift from using pedigree relationship matrices (A) to genomic ones. As the use of genomic relationship matrices (G) has increased, new methods to build or approximate G have developed. We investigated whether the way variance components are estimated should reflect these changes. We estimated variance components for maternal sow traits by solving with restricted maximum likelihood, with four methods of calculating the inverse of the relationship matrix. These methods included using just the inverse of A (A−1), combining A−1 and the direct inverse of G (HDIRECT−1), including metafounders (HMETA−1), or combining A−1 with an approximated inverse of G using the algorithm for proven and young animals (HAPY−1). There was a tendency for higher additive genetic variances and lower permanent environmental variances estimated with A−1 compared with the three H−1 methods, which supports that G−1 is better than A−1 at separating genetic and permanent environmental components, due to a better definition of the actual relationships between animals. There were limited or no differences in variance estimates between HDIRECT−1, HMETA−1, and HAPY−1. Importantly, there was limited differences in variance components, repeatability or heritability estimates between methods. Heritabilities ranged between <0.01 to 0.04 for stayability after second cycle, and farrowing rate, between 0.08 and 0.15 for litter weight variation, maximum cycle number, total number born, total number still born, and prolonged interval between weaning and first insemination, and between 0.39 and 0.44 for litter birth weight and gestation length. The limited differences in heritabilities suggest that there would be very limited changes to estimated breeding values or ranking of animals across models using the different sets of variance components. It is suggested that variance estimates continue to be made using A−1, however including G−1 is possibly more appropriate if refining the model, for traits that fit a permanent environmental effect.

Human Relationships with Domestic and Other Animals: One Health, One Welfare, One Biology

Excessive human population growth, uncontrolled use of natural resources, including deforestation, mining, wasteful systems, biodiversity reduction by agriculture, and damaging climate change affect the existence of all animals, including humans. This discussion is now urgent and people are rethinking their links with the animals we use for clothing, food, work, companionship, entertainment, and research. The concepts of one health, one welfare, and one biology are discussed as a background to driving global change. Nothing should be exploited without considering the ethics of the action and the consequences. This review concerns domesticated animals, including those used for human consumption of meat, eggs, and milk; horses kept for work; and dogs kept for company. Animal welfare includes health, emotional state, and comfort while moving and resting, and is affected by possibilities to show behavior and relationships with others of the same species or with humans. We show some examples of the relations between humans and domesticated animals in the environmental context, including zoonotic diseases, and consider the consequences and the new paradigms resulting from current awareness.

Genetics and genomics of uniformity and resilience in livestock and aquaculture species: A review

Genetic control of residual variance offers opportunities to increase uniformity and resilience of livestock and aquaculture species. Improving uniformity and resilience of animals will improve health and welfare of animals and lead to more homogenous products. Our aims in this review were to summarize the current models and methods to study genetic control of residual variance, genetic parameters and genomic results for residual variance and discuss future research directions. Typically, the genetic coefficient of variation is high (median = 0.27; range 0-0.86) and the heritability of residual variance is low (median = 0.01; range 0-0.10). Higher heritabilities can be achieved when increasing the number of records per animal. Divergent selection experiments have supported the feasibility of selecting for high or low residual variance. Genomic studies have revealed associations in regions related to stress, including those from the heat shock protein family. Although the number of studies is growing, genetic control of residual variance is still poorly understood, but big data and genomics offer great opportunities.

The effect of a porcine reproductive and respiratory syndrome outbreak on genetic parameters and reaction norms for reproductive performance in pigs1

The objective of this study was to estimate genetic parameters of antibody response and reproductive traits after exposure to porcine reproductive and respiratory syndrome virus. Blood samples were taken approximately 60 d after the outbreak. Antibody levels were quantified as the sample-to-positive ratio (S/P ratio) using a fluorescent microsphere assay. Reproductive traits included total number born (TNB), number born alive (NBA), number stillborn (NSB), number mummified (NBM), and number born dead (NBD). Mortality traits were log transformed for genetic analyses. Data were split into prior, during, and after the disease outbreak phases using visual appraisal of the estimates of farm-year-week effects for each reproductive trait. For NBA, data from all phases were combined into a reaction norm analysis with regression on estimates of farm-year-week effects for NBA. Heritability for S/P ratio was estimated at 0.17 ± 0.05. Heritability estimates for reproduction traits were all low and were lower during the outbreak for NBA but greater for mortality traits. TNB was not greatly affected during the outbreak, as many sows that farrowed during the outbreak were mated prior to the outbreak. Heritability for TNB decreased from 0.13 (prior) to 0.08 (after). Genetic correlation estimates between prior to and during the outbreak were high for TNB (0.86 ± 0.23) and NBA (0.98 ± 0.38) but lower for mortality traits: 0.65 ± 0.43, −0.42 ± 0.55, and 0.29 ± 1.39 for LNSB, LNBM, and LNBD, respectively. TNB prior to and after the outbreak had a lower genetic correlation (0.32 ± 0.33). In general, genetic correlation estimates of S/P ratio with reproductive performance during the outbreak were below 0.20 in absolute value, except for LNSB (−0.73 ± 0.29). Based on the reaction norm model, estimates of genetic correlations between the intercept and slope terms ranged from 0.24 ± 0.50 to 0.54 ± 0.35 depending on the parameterization used, indicating that selection for the intercept may result in indirect selection for steeper slopes, and thus, less resilient animals. In general, estimates of genetic correlations between farm-year-week effect classes based on the reaction norm model resembled estimates of genetic correlations from the multivariate analysis. Overall, compared to previous studies, antibody S/P ratios showed a lower heritability (0.17 ± 0.05) and low genetic correlations with reproductive performance during a porcine reproductive and respiratory syndrome outbreak, except for the LNSB.

Genotype by feed interaction for feed efficiency and growth performance traits in pigs

A major objective of pork producers is to reduce production cost. Feeding may account for over 75% of pork production costs. Thus, selecting pigs for feed efficiency (FE) traits is a priority in pig breeding programs. While in the Americas, pigs are typically fed high-input diets, based on corn and soybean meal (CS); in Western Europe, pigs are commonly fed diets based on wheat and barley with high amounts of added protein-rich coproducts (WB), e.g., from milling and seed-oil industries. These two feeding scenarios provided a realistic setting for investigating a specific type of genotype by environment interaction; thus, we investigated the genotype by feed interaction (GxF). In the presence of a GxF, different feed compositions should be considered when selecting for FE. This study aimed to 1) verify the presence of a GxF for FE and growth performance traits in different growth phases (starter, grower, and finisher) of 3-way crossbred growing-finishing pigs fed either a CS (547 boars and 558 gilts) or WB (567 boars and 558 gilts) diet; and 2) to assess and compare the expected responses to direct selection under the 2 diets and the expected correlated responses for one diet to indirect selection under the other diet. We found that GxF did not interfere in the ranking of genotypes under both diets for growth, protein deposition, feed intake, energy intake, or feed conversion rate. Therefore, for these traits, we recommend changing the diet of growing-finishing pigs from high-input feed (i.e., CS) to feed with less valuable ingredients, as WB, to reduce production costs and the environmental impact, regardless of which diet is used in selection. We found that GxF interfered in the ranking of genotypes and caused heterogeneity of genetic variance under both diets for lipid deposition (LD), residual energy intake (REI), and residual feed intake (RFI). Thus, selecting pigs under a diet different from the diet used for growing-finishing performance could compromise the LD in all growth phases, compromise the REI and RFI during the starter phase, and severely compromise the REI during the grower phase. In particular, when pigs are required to consume a WB diet for growing-finishing performance, pigs should be selected for FE under the same diet. Breeding pigs for FE under lower-input diets should be considered, because FE traits will become more important and lower-input diets will become more widespread in the near future.

Selection on resilience improves disease resistance and tolerance to infections

Response to infection in animals has 2 main mechanisms: resistance (ability to control pathogen burden) and tolerance (ability to maintain performance given the pathogen burden). Selection on disease resistance and tolerance to infections seems a promising avenue to increase productivity of animals in the presence of disease infections, but it is hampered by a lack of records of pathogen burden of infected animals. Selection on resilience (ability to maintain performance regardless of pathogen burden) may, therefore, be an alternative pragmatic approach, because it does not need records of pathogen burden. Therefore, the aim of this study was to assess response to selection in resistance and tolerance when selecting on resilience compared with direct selection on resistance and tolerance. Monte Carlo simulation was used combined with selection index theory to predict responses to selection. Using EBV for resilience in the absence of records for pathogen burden resulted in favorable responses in resistance and tolerance to infections, with higher responses in tolerance than in resistance. If resistance and tolerance were unfavorably correlated, lower selection responses were obtained, especially in resistance. When the genetic correlation was very unfavorable, the selection response in tolerance became negative. Results showed that lower selection responses in resistance and tolerance were obtained when the frequency of disease outbreaks was 10% rather than 50% of the contemporary groups. The efficiency of selection on EBV for resilience compared with selection on EBV for resistance and tolerance was, however, not affected by the frequency of disease outbreaks. When records on pathogen burden were available, selection responses in resistance, tolerance, and the total breeding goal were 3 to 28%, 66 to 398%, and 2 to 11% higher, respectively, than when using the EBV for resilience, showing a clear benefit of recording pathogen burden. This study shows that selection on resilience is a pragmatic way of increasing disease resistance and tolerance to infections in the absence of records on pathogen burden, but recording pathogen burden would yield higher selection responses in resistance and tolerance.