Meat quality is an important trait for pig-breeding programs aiming to meet consumers’ demands. Geneticists must improve meat quality based on their understanding of the underlying genetic mechanisms. Previous studies showed that most meat-quality indicators were low-to-moderate heritability traits; therefore, improving meat quality using conventional techniques remains a challenge. Here, we performed a genome-wide association study of meat-quality traits using the GeneSeek Porcine SNP50K BeadChip in 582 crossbred Duroc × (Landrace × Yorkshire) commercial pigs (249 males and 333 females). Meat conductivity, marbling score, moisture, meat color, pH, and intramuscular fat (IMF) content were investigated. The genome-wide association study was performed using both fixed and random model Circulating Probability Unification (FarmCPU) and a mixed linear model (MLM) with the rMVP software. The genomic heritability of the studied traits ranged from 0.13 ± 0.07 to 0.55 ± 0.08 for conductivity and meat color, respectively. Thirty-two single-nucleotide polymorphisms (SNPs) were identified for meat quality in the crossbred pigs using both FarmCPU and MLM. Among the detected SNPs, five, nine, seven, four, six, and five were significantly associated with conductivity, IMF, marbling score, meat color, moisture, and pH, respectively. Several candidate genes for meat quality were identified in the detected genomic regions. These findings will contribute to the ongoing improvement of meat quality, meeting consumer demands and improving the economic outlook for the swine industry.

Understanding the molecular and cellular mechanisms underlying complex traits in pigs is crucial for enhancing genetic gain via artificial selection and utilizing pigs as models for human disease and biology. Here, we conducted comprehensive genome-wide association studies (GWAS) followed by a cross-breed meta-analysis for 232 complex traits and a within-breed meta-analysis for 12 traits, using 28.3 million imputed sequence variants in 70 328 animals across 14 pig breeds. We identified 6878 quantitative trait loci (QTL) for 139 complex traits. Leveraging the Pig Genotype-Tissue Expression resource, we systematically investigated the biological context and regulatory mechanisms behind these trait-QTLs, ultimately prioritizing 14 829 variant-gene-tissue-trait regulatory circuits. For instance, rs344053754 regulates UGT2B31 expression in the liver and intestines, potentially by modulating enhancer activity, ultimately influencing litter weight at weaning in pigs. Furthermore, we observed conservation of certain genetic and regulatory mechanisms underlying complex traits between humans and pigs. Overall, our cross-breed meta-GWAS in pigs provides invaluable resources and novel insights into the genetic regulatory and evolutionary mechanisms of complex traits in mammals.

The gut microbial composition of the Luchuan (LC) piglet, one of China’s native breeds, has rarely been studied, especially when compared to other breeds. This study developed a porcine epidemic diarrhea virus (PEDV) infection model in LC and Largewhite (LW) piglets, and analyzed the patterns and differences of intestinal microbial communities and metabolites in piglets of these two breeds after infection. The diarrhea score, survival time, and distribution of viral antigens in the intestine of piglets infected with PEDV differed among breeds, with the jejunal immunohistochemistry score of LW piglets being significantly higher than that of LC piglets (P < 0.001). The results of 16S rRNA sequencing showed differences in microbial diversity and community composition in the intestine of piglets with different breeds between PEDV infection piglets and the healthy controls. There were differences in the species and number of dominant phyla and dominant genera in the same intestinal segment. The relative abundance of Shigella in the jejunum of LC piglets after PEDV infection was significantly lower than that of LW piglets (P < 0.05). The key microorganisms differed in the microbiota were Streptococcus alactolyticus, Roseburia faecis, Lactobacillus iners, Streptococcus equi, and Lactobacillus mucosae (P < 0.05). The non-targeted metabolite analysis revealed that intestinal metabolites showed great differences among the different breeds related to infection. Spearman correlation analysis was conducted to examine any links between the microbiota and metabolites. The metabolites in the intestine of different breeds related to infection were mainly involved in arginine biosynthesis, synaptic vesicle cycle, nicotinic acid and nicotinamide metabolism and mTOR signaling pathway, with significantly positive or negative correlations (P < 0.05) between the various microorganisms. This study provides a theoretical foundation for investigating the application of core microorganisms in the gut of piglets of different breeds in the digestive tracts of those infected with PEDV, and helps to tackle the antimicrobial resistance problem further.

Gut microbiota plays a crucial role in the health and productivity of pigs. However, the spread of antibiotic resistance genes (ARGs) and viruses within the pig intestinal microbiota poses significant threats to animal and public health. This study utilized 181 pig samples from nine European countries and employed metagenomic assembly methods to investigate the dynamics and distribution of ARGs and viruses within the pig intestinal microbiota, aiming to observing their associations with potential bacterial hosts. We identified 4605 metagenome-assembled genomes (MAGs), corresponding to 19 bacterial phyla, 97 families, 309 genera, and a total of 449 species. Additionally, 44 MAGs were classified as archaea. Analysis of ARGs revealed 276 ARG types across 21 ARG classes, with Glycopeptide being the most abundant ARG class, followed by the class of Multidrug. Treponema D sp016293915 was identified as a primary potential bacterial host for Glycopeptide. Aligning nucleotide sequences with a viral database, we identified 1044 viruses. Among the viral genome families, Peduoviridae and Intestiviridae were the most prevalent, with CAG-914 sp000437895 being the most common potential host species for both. These findings highlight the importance of MAGs in enhancing our understanding of the gut microbiome, revealing microbial diversity, antibiotic resistance, and virus–bacteria interactions. The data analysis for the article was based on the public dataset PRJEB22062 in the European Nucleotide Archive.

High-fiber, low-cost agricultural byproducts offer a sustainable alternative for mitigating the competition for crops between humans and livestock. Pigs predominantly utilize dietary fibers through the process of microbial fermentation within the gut. This study explored the gut microbiota and the capacity for carbohydrate degradation in 30 individual Lantang pigs, a breed indigenous to China. Through metagenomic analysis, a total of 671 metagenome-assembled genomes (MAGs) were assembled and assigned into 14 bacterial and 1 archaeal phylum, including 97 species from uncultured microbes. The phylum with the highest abundance were identified as Bacillota_A, Bacteroidota, and Bacillota. Remarkably, the investigation revealed nearly 10,000 genes implicated in the degradation of carbohydrates, with a pronounced prevalence within five principal bacterial genera: Prevotella, Cryptobacteroides, Gemmiger, Vescimonas, and Faecousia. Additionally, 87 distinct types of carbohydrate-degrading enzymes were exclusively identified within the gut microbiota of the Lantang pig. These insights not only enhance our understanding of the microbial diversity specific to native Chinese pig breeds but also augment the body of research regarding porcine fiber degradation capabilities. The implications of this study are twofold: it provides strategic directions for optimizing feed efficiency and reducing breeding costs, and it furnishes an expanded gene pool for the microbial synthesis of industrial enzymes in the future.