Genotype by environment interactions for performance and thermoregulation responses in growing pigs1,2

Identification and characterization of unknown disturbances in a structured population using high-throughput phenotyping data and measurement of robustness: application to growing pigs

Improving the robustness of animals has become a priority in breeding due to climate change, new societal demands, and the agroecological transition. Components of animal robustness can be extracted from the analysis of the adaptive response of an animal to disturbance using longitudinal data. Nonetheless, this response is a function of animal robustness as well as of disturbance characteristics (intensity and duration). To correctly assess an animal's robustness potential, it is therefore useful to know the characteristics of the disturbances it faces. The UpDown method, which detects and characterizes unknown disturbances at different levels of organization of the population (e.g., individual, pen, and batch disturbances), has been proposed for this purpose. Furthermore, using the outputs of the method, it is possible to extract proxies of the robustness of animals. In this context, the objective of the study was to evaluate the performances of the UpDown method to detect and characterize disturbances and quantify the robustness of animals in a genetic framework using different sets of simulations, and to apply this method to real pig longitudinal data recorded during the fattening period (body weight, cumulative feed intake, and feeding rate). Based on the simulations, the specificity of the UpDown method was high (>0.95). Its sensitivity increased with the level of organization exposed (from 0.23 to 0.32 for individual disturbances, from 0.45 to 0.59 for pen disturbances, and from 0.77 to 0.88 for batch disturbances). The UpDown method also showed a good ability to characterize detected disturbances. The average time interval between the estimated and true start date or duration of the disturbance was lower than 3 d. The correlation between the true and estimated intensity of the disturbance increased with the hierarchical level of organization (on average, 0.41, 0.78, and 0.83 for individual, pen, and batch disturbance, respectively). The accuracy of the estimated breeding values of the proxies for robustness extracted from the analysis of individual trajectories over time were moderate (lower than 0.33). Applied to real data, the UpDown method detected different disturbances depending on the phenotype analyzed. The heritability of the proxies of robustness were low to moderate (ranging from 0.11 to 0.20).

Investigating the impact of non-additive genetic effects in the estimation of variance components and genomic predictions for heat tolerance and performance traits in crossbred and purebred pig populations

BACKGROUND

Non-additive genetic effects are often ignored in livestock genetic evaluations. However, fitting them in the models could improve the accuracy of genomic breeding values. Furthermore, non-additive genetic effects contribute to heterosis, which could be optimized through mating designs. Traits related to fitness and adaptation, such as heat tolerance, tend to be more influenced by non-additive genetic effects. In this context, the primary objectives of this study were to estimate variance components and assess the predictive performance of genomic prediction of breeding values based on alternative models and two independent datasets, including performance records from a purebred pig population and heat tolerance indicators recorded in crossbred lactating sows.

RESULTS

Including non-additive genetic effects when modelling performance traits in purebred pigs had no effect on the residual variance estimates for most of the traits, but lower additive genetic variances were observed, especially when additive-by-additive epistasis was included in the models. Furthermore, including non-additive genetic effects did not improve the prediction accuracy of genomic breeding values, but there was animal re-ranking across the models. For the heat tolerance indicators recorded in a crossbred population, most traits had small non-additive genetic variance with large standard error estimates. Nevertheless, panting score and hair density presented substantial additive-by-additive epistatic variance. Panting score had an epistatic variance estimate of 0.1379, which accounted for 82.22% of the total genetic variance. For hair density, the epistatic variance estimates ranged from 0.1745 to 0.1845, which represent 64.95-69.59% of the total genetic variance.

CONCLUSIONS

Including non-additive genetic effects in the models did not improve the accuracy of genomic breeding values for performance traits in purebred pigs, but there was substantial re-ranking of selection candidates depending on the model fitted. Except for panting score and hair density, low non-additive genetic variance estimates were observed for heat tolerance indicators in crossbred pigs.

Identification of intestinal and fecal microbial biomarkers using a porcine social stress model

Understanding the relationships between social stress and the gastrointestinal microbiota, and how they influence host health and performance is expected to have many scientific and commercial implementations in different species, including identification and improvement of challenges to animal welfare and health. In particular, the study of the stress impact on the gastrointestinal microbiota of pigs may be of interest as a model for human health. A porcine stress model based on repeated regrouping and reduced space allowance during the last 4 weeks of the finishing period was developed to identify stress-induced changes in the gut microbiome composition. The application of the porcine stress model resulted in a significant increase in salivary cortisol concentration over the course of the trial and decreased growth performance and appetite. The applied social stress resulted in 32 bacteria being either enriched (13) or depleted (19) in the intestine and feces. Fecal samples showed a greater number of microbial genera influenced by stress than caecum or colon samples. Our trial revealed that the opportunistic pathogens Treponema and Clostridium were enriched in colonic and fecal samples from stressed pigs. Additionally, genera such as Streptococcus, Parabacteroides, Desulfovibrio, Terrisporobacter, Marvinbryantia, and Romboutsia were found to be enriched in response to social stress. In contrast, the genera Prevotella, Faecalibacterium, Butyricicoccus, Dialister, Alloprevotella, Megasphaera, and Mitsuokella were depleted. These depleted bacteria are of great interest because they synthesize metabolites [e.g., short-chain fatty acids (SCFA), in particular, butyrate] showing beneficial health benefits due to inhibitory effects on pathogenic bacteria in different animal species. Of particular interest are Dialister and Faecalibacterium, as their depletion was identified in a human study to be associated with inferior quality of life and depression. We also revealed that some pigs were more susceptible to pathogens as indicated by large enrichments of opportunistic pathogens of Clostridium, Treponema, Streptococcus and Campylobacter. Generally, our results provide further evidence for the microbiota-gut-brain axis as indicated by an increase in cortisol concentration due to social stress regulated by the hypothalamic-pituitary-adrenal axis, and a change in microbiota composition, particularly of bacteria known to be associated with pathogenicity and mental health diseases.

Association analysis of mitochondrial genome polymorphisms with backfat thickness in pigs

Mitochondrial DNA (mtDNA) variations and associated effects on economic traits have been widely reported in farm animals, as these genetic polymorphisms can affect the efficiency of energy production and cell metabolism. In studies related to metabolism, the deposition of fat was highly correlated with mitochondria. However, the effect of mtDNA polymorphisms on porcine backfat thickness (BFT) remained unclear. In this study, 243 pigs were collected to analyse the relationship between BFT and mtDNA polymorphisms. There were considerable differences in BFT, ranging from 5 mm to 18 mm. MtDNA D-loop sequencing discovered 48 polymorphic sites. Association analysis revealed that 30 variations were associated with BFT (P < 0.05). The polymorphism m.794A > G showed the maximum difference in BFT between A and G carriers, which differed at ∼2.5 mm (P < 0.001). The 48 polymorphic sites generated 22 haplotypes (H1-H22), which clustered into 4 haplogroups (HG1-HG4). HG1 had a lower BFT value than other three haplogroups (P < 0.01), whereas H4 in HG1 exhibited the lowest BFT of all haplotypes analyzed (P < 0.01). The results of this study highlight an association between mtDNA polymorphisms and BFT, and suggest the potential application of mtDNA in pig molecular breeding practices.

Genetic parameters for automatically-measured vaginal temperature, respiration efficiency, and other thermotolerance indicators measured on lactating sows under heat stress conditions

BACKGROUND

Genetic selection based on direct indicators of heat stress could capture additional mechanisms that are involved in heat stress response and enable more accurate selection for more heat-tolerant individuals. Therefore, the main objectives of this study were to estimate genetic parameters for various heat stress indicators in a commercial population of Landrace × Large White lactating sows measured under heat stress conditions. The main indicators evaluated were: skin surface temperatures (SST), automatically-recorded vaginal temperature (TV), respiration rate (RR), panting score (PS), body condition score (BCS), hair density (HD), body size (BS), ear size, and respiration efficiency (Reff).

RESULTS

Traits based on TV presented moderate heritability estimates, ranging from 0.15 ± 0.02 to 0.29 ± 0.05. Low heritability estimates were found for SST traits (from 0.04 ± 0.01 to 0.06 ± 0.01), RR (0.06 ± 0.01), PS (0.05 0.01), and Reff (0.03 ± 0.01). Moderate to high heritability values were estimated for BCS (0.29 ± 0.04 for caliper measurements and 0.25 ± 0.04 for visual assessments), HD (0.25 ± 0.05), BS (0.33 ± 0.05), ear area (EA; 0.40 ± 0.09), and ear length (EL; 0.32 ± 0.07). High genetic correlations were estimated among SST traits (> 0.78) and among TV traits (> 0.75). Similarly, high genetic correlations were also estimated for RR with PS (0.87 ± 0.02), with BCS measures (0.92 ± 0.04), and with ear measures (0.95 ± 0.03). Low to moderate positive genetic correlations were estimated between SST and TV (from 0.25 ± 0.04 to 0.76 ± 0.07). Low genetic correlations were estimated between TV and BCS (from - 0.01 ± 0.08 to 0.06 ± 0.07). Respiration efficiency was estimated to be positively and moderately correlated with RR (0.36 ± 0.04), PS (0.56 ± 0.03), and BCS (0.56 ± 0.05 for caliper measurements and 0.50 ± 0.05 for the visual assessments). All other trait combinations were lowly genetically correlated.

CONCLUSIONS

A comprehensive landscape of heritabilities and genetic correlations for various thermotolerance indicators in lactating sows were estimated. All traits evaluated are under genetic control and heritable, with different magnitudes, indicating that genetic progress is possible for all of them. The genetic correlation estimates provide evidence for the complex relationships between these traits and confirm the importance of a sub-index of thermotolerance traits to improve heat tolerance in pigs.

Accounting for overlapping annotations in genomic prediction models of complex traits

Background

It is now widespread in livestock and plant breeding to use genotyping data to predict phenotypes with genomic prediction models. In parallel, genomic annotations related to a variety of traits are increasing in number and granularity, providing valuable insight into potentially important positions in the genome. The BayesRC model integrates this prior biological information by factorizing the genome according to disjoint annotation categories, in some cases enabling improved prediction of heritable traits. However, BayesRC is not adapted to cases where markers may have multiple annotations.

Results

We propose two novel Bayesian approaches to account for multi-annotated markers through a cumulative (BayesRC+) or preferential (BayesRC\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pi$$\end{document}π) model of the contribution of multiple annotation categories. We illustrate their performance on simulated data with various genetic architectures and types of annotations. We also explore their use on data from a backcross population of growing pigs in conjunction with annotations constructed using the PigQTLdb. In both simulated and real data, we observed a modest improvement in prediction quality with our models when used with informative annotations. In addition, our results show that BayesRC+ successfully prioritizes multi-annotated markers according to their posterior variance, while BayesRC\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pi$$\end{document}π provides a useful interpretation of informative annotations for multi-annotated markers. Finally, we explore several strategies for constructing annotations from a public database, highlighting the importance of careful consideration of this step.

Conclusion

When used with annotations that are relevant to the trait under study, BayesRC\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pi$$\end{document}π and BayesRC+ allow for improved prediction and prioritization of multi-annotated markers, and can provide useful biological insight into the genetic architecture of traits.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04914-5.

Strategies for Hypothermia Compensation in Altricial and Precocial Newborn Mammals and Their Monitoring by Infrared Thermography

Thermoregulation in newborn mammals is an essential species-specific mechanism of the nervous system that contributes to their survival during the first hours and days of their life. When exposed to cold weather, which is a risk factor associated with mortality in neonates, pathways such as the hypothalamic–pituitary–adrenal axis (HPA) are activated to achieve temperature control, increasing the circulating levels of catecholamine and cortisol. Consequently, alterations in blood circulation and mechanisms to produce or to retain heat (e.g., vasoconstriction, piloerection, shivering, brown adipocyte tissue activation, and huddling) begin to prevent hypothermia. This study aimed to discuss the mechanisms of thermoregulation in newborn domestic mammals, highlighting the differences between altricial and precocial species. The processes that employ brown adipocyte tissue, shivering, thermoregulatory behaviors, and dermal vasomotor control will be analyzed to understand the physiology and the importance of implementing techniques to promote thermoregulation and survival in the critical post-birth period of mammals. Also, infrared thermography as a helpful method to perform thermal measurements without animal interactions does not affect these parameters.

Plasticity of feeding behaviour traits in response to production environment (temperate vs. tropical) in group-housed growing pigs

Heat stress affects pig metabolism, health and welfare, resulting in reduced growth and important economic losses. The present experiment aimed to evaluate the effects of two climatic environments [temperate (TEMP) vs. tropical humid (TROP)] on feeding behaviour in growing pigs. The feeding behaviour traits were measured with automated feeders and included: daily feed intake, daily eating time, feeding rate, daily number of meals, feed intake per meal, and feeding time per meal. Pigs came from a backcross population between Large White (LW, heat sensitive) and Creole (CR, heat tolerant) pigs. The same 10 F1 LW × CR boars (sire families [SF]) were mated with related LW sows in each environment. Feeding behaviour was recorded for a total of 1,296 pigs (n = 634 pigs for TEMP and n = 662 pigs for TROP) between 11 and 23 weeks of age. Growth performance and thermoregulatory responses (rectal and skin temperatures) were also measured. Results show that TROP conditions affect feeding behaviour traits: animals had more meals per day but these meals were smaller both in duration and in size, resulting in lower daily feed intake and less time eating per day. Significant SF by environment (GxE) interactions were found for all feeding behaviour traits. When SF were distributed into robust and sensitive groups (previously defined according to performance and thermoregulatory traits), results showed group by environment interactions for all feeding traits, except meal frequency. Moreover, a significant difference in feeding rate between robust and sensitive group was detected in TEMP, suggesting that feeding rate may be a good candidate to evaluate heat tolerance.

Effect of ambient temperature on average daily gain of pigs evaluated using public weather data and a plateau-linear regression model

We performed a plateau-linear regression model analysis of the average daily gain (ADG) of pigs on daily average temperature at the end of performance testing (T). Records for performance testing between 30 kg and 105 kg of 2268 purebred Duroc pigs raised at the National Livestock Breeding Center Miyazaki Station were used. Off-farm ambient temperatures were measured at the nearest Automated Meteorological Data Acquisition System station at Kobayashi, Miyazaki (Kobayashi station). A plateau-linear regression equation was obtained in which ADG decreased by 12.6 g for every 1°C when T > 21.1°C. We calculated the expected age in day at the end of testing (D105) using the regression equation obtained and T observed at the Kobayashi station in 2020. The number of days that D105 was prolonged due to higher T was 125 days, corresponding to approximately one third of the year. These results could contribute to planning and management of stable pork production in response to heat in Japan.

The Genetics of Thermoregulation in Pigs: A Review

Heat stress (HS) affects pig performance, health and welfare, resulting in a financial burden to the pig industry. Pigs have a limited number of functional sweat glands and their thermoregulatory mechanisms used to maintain body temperature, are challenged by HS to maintain body temperature. The genetic selection of genotypes tolerant to HS is a promising long-term (adaptation) option that could be combined with other measures at the production system level. This review summarizes the current knowledge on the genetics of thermoregulation in pigs. It also discusses the different phenotypes that can be used in genetic studies, as well as the variability in thermoregulation between pig breeds and the inheritance of traits related to thermoregulation. This review also considers on-going challenges to face for improving heat tolerance in pigs.

Effects of Ambient Temperature on the Performance and Thermoregulatory Responses of Commercial and Crossbred (Brazilian Piau Purebred Sires × Commercial Dams) Growing-Finishing Pigs

Simple Summary

Physiological responses to heat stress are affected by breed. Therefore, crossbreeding genetically improved lines with tropically adapted breeds of pigs may be a strategy to attenuate the impact of high ambient temperatures on pig production. Although some studies have evaluated thermotolerance in tropically adapted breeds, it is not yet clear to which extent improved tolerance to heat stress is a consequence of a greater ability to equilibrate thermogenesis and thermolysis, or if it is a consequence of decreased growth performance. Although there was no interaction for performance, thermoregulatory responses, and blood parameters, our results evidenced that ambient temperature effects on carcass parameters were modulated by the pigs’ genotype. Because protein deposition significantly decreased in response to high ambient temperature in commercial pigs, and was not affected by ambient temperature in Piau crossbred pigs, our study suggests increased thermotolerance of Piau crossbred pigs.

Abstract

The study aimed at evaluating the effects of high ambient temperature (HT: 30 °C) on the thermoregulatory responses and performance of commercial and Piau crossbred (Brazilian Piau breed sires × commercial genotype dams) growing pigs. Commercial and Piau crossbred pigs were reared under thermoneutral (TN: 22 °C) or HT conditions during a 14-day experimental period. Feeding (daily) and animals (beginning and end) were weighted to obtain performance parameters. Skin and rectal temperatures, respiratory rate, and blood parameters were also measured. At the end of the trial (day 15), the animal’s backfat thickness (BF) and loin eye area (LEA) were measured. No interaction (p > 0.05) between the genetic group and ambient temperature was observed for any performance trait. Irrespective of ambient temperature, Piau crossbred pigs had a similar feed intake (ADFI, 2615 g/day, on average; p > 0.05), lower daily weight gain (ADG, −234 g/day; p < 0.01), and a higher feed conversion ratio (FCR, +0.675 g/g; p < 0.01). There was interaction (p = 0.01) between genotype and ambient temperature for the LEA that decreased significantly in response to HT in commercial pigs (−6.88 cm²) and did not differ in response to ambient temperature in Piau crossbred pigs (29.14 cm², on average; p > 0.05). Piau crossbred pigs had greater BF (+7.2 mm; p < 0.01) than commercial pigs. Regardless of the genetic group, exposure of pigs to HT resulted in decreased ADFI (−372 g/day; p < 0.01), ADG (−185 g/day; p < 0.01), and a higher FCR (+0.48 g/g; p = 0.01). Ambient temperature did not affect lipid deposition. Pigs at HT had an increased respiratory rate (+38 bpm; p < 0.01) and a long-lasting increase in skin and rectal temperatures compared to TN pigs. Total concentrations of triiodothyronine (T₃) and thyroxine (T₄) were not affected by ambient temperature in commercial pigs, whereas Piau crossbred pigs kept at 30 °C had a transient decrease in both hormones at day 2 (p < 0.01). Serum cortisol concentrations were not affected (p > 0.05) by genotype nor ambient temperature. In summary, Piau crossbred pigs had lower efficiency using nutrients for growth in association with increased lipid deposition when compared to commercial pigs. In response to HT, commercial pigs had a decreased LEA, whereas no effect was observed for Piau crossbred pigs. Apart from that, commercial and Piau crossbred pigs had a similar magnitude of thermoregulatory responses activation in response to HT, evidencing their innate survival-oriented function.

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.

Agroecological practices to support tropical livestock farming systems: a Caribbean and Latin American perspective

With global climate changes currently occurring, and particularly given the severe energy and food shortages occurring throughout tropical regions, agroecological (AE) systems are drawing renewed attention as an efficient alternative to intensive models of production, particularly unsuitable in regions of the world such as the Caribbean or Latin America. There is a pressing need to focus on livestock farming systems (LFS) and characterize their potential contributions to global sustainability. A multidisciplinary approach is needed to address these multiple and complex problems. Traditionally, LFS have shown their sustainability high potential. The purpose of this work is to highlight solutions to minimize inputs, by describing some success and diverse case studies through the Caribbean. These systems were analyzed at different levels: animal/function, farm/family, and territory/society. This produced a set of guidelines that help to increase the efficiency of tropical systems, particularly those concerned with (1) choosing the best-suited genotypes, while enhancing population biodiversity; (2) matching the farming system to the available resources, feed, and by-products; (3) steering the whole farming system through reproduction management with no hormonal treatment, while facilitating system reproducibility and increasing performances; (4) controlling health constraints instead of annihilating risks and implement an integrated management design to reduce chemical treatments or increase the use of nutraceuticals; and (5) mitigating climate constraints by using soft techniques. In the second part of this work, some integrated systems are described. The Tosoly farm of Colombia, for instance, is conceived as a totally integrated crop-livestock system, allowing the additional production of energy at the farm level. Thus, it epitomizes the positive impact that livestock can exert upon the environment. The case study of Haiti indicates how AE practices can help in designing a pro-poor sustainable milk production system. It concerns an entire dairy sector built all over the country on the basis of micro-units of milk production and processing.