A first characterization of the microbiota-resilience link in swine.

BACKGROUND: The gut microbiome plays a crucial role in understanding complex biological mechanisms, including host resilience to stressors. Investigating the microbiota-resilience link in animals and plants holds relevance in addressing challenges like adaptation of agricultural species to a warming environment. This study aims to characterize the microbiota-resilience connection in swine. As resilience is not directly observable, we estimated it using four distinct indicators based on daily feed consumption variability, assuming animals with greater intake variation may face challenges in maintaining stable physiological status. These indicators were analyzed both as linear and categorical variables. In our first set of analyses, we explored the microbiota-resilience link using PERMANOVA, α-diversity analysis, and discriminant analysis. Additionally, we quantified the ratio of estimated microbiota variance to total phenotypic variance (microbiability). Finally, we conducted a Partial Least Squares-Discriminant Analysis (PLS-DA) to assess the classification performance of the microbiota with indicators expressed in classes. RESULTS: This study offers four key insights. Firstly, among all indicators, two effectively captured resilience. Secondly, our analyses revealed robust relationship between microbial composition and resilience in terms of both composition and richness. We found decreased α-diversity in less-resilient animals, while specific amplicon sequence variants (ASVs) and KEGG pathways associated with inflammatory responses were negatively linked to resilience. Thirdly, considering resilience indicators in classes, we observed significant differences in microbial composition primarily in animals with lower resilience. Lastly, our study indicates that gut microbial composition can serve as a reliable biomarker for distinguishing individuals with lower resilience. CONCLUSION: Our comprehensive analyses have highlighted the host-microbiota and resilience connection, contributing valuable insights to the existing scientific knowledge. The practical implications of PLS-DA and microbiability results are noteworthy. PLS-DA suggests that host-microbiota interactions could be utilized as biomarkers for monitoring resilience. Furthermore, the microbiability findings show that leveraging host-microbiota insights may improve the identification of resilient animals, supporting their adaptive capacity in response to changing environmental conditions. These practical implications offer promising avenues for enhancing animal well-being and adaptation strategies in the context of environmental challenges faced by livestock populations. Video Abstract.

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.

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.

Gut microbiome composition differences among breeds impact feed efficiency in swine.

BACKGROUND: Feed efficiency is a crucial parameter in swine production, given both its economic and environmental impact. The gut microbiota plays an essential role in nutrient digestibility and is, therefore, likely to affect feed efficiency. This study aimed to characterize feed efficiency, fatness traits, and gut microbiome composition in three major breeds of domesticated swine and investigate a possible link between feed efficiency and gut microbiota composition. RESULTS: Average daily feed intake (ADFI), average daily gain (ADG), feed conversion ratio (FCR), residual feed intake (RFI), backfat, loin depth, and intramuscular fat of 615 pigs belonging to the Duroc (DR), Landrace (LR), and Large White (LW) breeds were measured. Gut microbiota composition was characterized by 16S rRNA gene sequencing. Orthogonal contrasts between paternal line (DR) and maternal lines (LR+LW) and between the two maternal lines (LR versus LW) were performed. Average daily feed intake and ADG were statistically different with DR having lower ADFI and ADG compared to LR and LW. Landrace and LW had a similar ADG and RFI, with higher ADFI and FCR for LW. Alpha diversity was higher in the fecal microbial communities of LR pigs than in those of DR and LW pigs for all time points considered. Duroc communities had significantly higher proportional representation of the Catenibacterium and Clostridium genera compared to LR and LW, while LR pigs had significantly higher proportions of Bacteroides than LW for all time points considered. Amplicon sequence variants from multiple genera (including Anaerovibrio, Bacteroides, Blautia, Clostridium, Dorea, Eubacterium, Faecalibacterium, Lactobacillus, Oscillibacter, and Ruminococcus) were found to be significantly associated with feed efficiency, regardless of the time point considered. CONCLUSIONS: In this study, we characterized differences in the composition of the fecal microbiota of three commercially relevant breeds of swine, both over time and between breeds. Correlations between different microbiome compositions and feed efficiency were established. This suggests that the microbial community may contribute to shaping host productive parameters. Moreover, our study provides important insights into how the intestinal microbial community might influence host energy harvesting capacity. A deeper understanding of this process may allow us to modulate the gut microbiome in order to raise more efficient animals. Video Abstract.

Selenium in soils, spermatophytes and bryophytes around a Zn-Pb smelter, New South Wales, Australia.

Selenium concentrations and its spatial distribution in soils, spermatophytes and bryophytes (mosses) around the Cockle Creek Zn-Pb smelter, New South Wales were studied from May to November 2000. Selenium was determined by ICP-MS on soils digested in nitric and hydrochloric acid (HNO3:HCl = 3:1), and plant samples digested in distilled concentrated nitric acid. At distances greater than 3 km, selenium in soils, spermatophytes and bryophytes converge to uniform values, which are considered to represent the background value. Mean selenium in soils around the smelter is two times higher than the background value. Mean concentration of selenium in plants around the smelter is three times greater than that for background plants. Selenium from 'in site' bryophyte is twice that found in the background bryophyte. The transfer coefficients of selenium between plants and soils are low, especially at a distance less than 1 km from the smelter. However, mosses show the reverse trend. This study indicates that the Zn-Pb smelter is one of the anthropogenic point sources of selenium pollution in the Lake Macquarie district.