Intestinal probiotics significantly regulate the growth performance of their host, with their composition being influenced by various factors. While many studies have explored how gut microbiota composition affects growth traits such as body weight and BMI, the research on probiotics influenced by host genetic factors, and their subsequent impact on host growth performance, remains limited. To address this research gap, we collected fecal and tissue samples, as well as phenotypic data, from 193 Yunong black pigs at 280 days of age. We then sequenced and genotyped all 193 subjects using the 50K SNP BeadChip, yielding a comprehensive dataset for genetic and microbiome analyses. We then employed microbiome-wide association studies (MWAS), a meta-analysis, and microbiome-wide genetic association studies (MGWASs) to examine the relationship between host genetics, gut microbiota, and growth performance. Four key microbial taxa, namely Coprococcus, Blautia, Ruminococcaceae, and RF16, were identified as being significantly associated with body weight and BMI. The MGWAS analysis revealed that both Coprococcus and Ruminococcaceae were significantly associated with host genomic variations. A total of four important single nucleotide polymorphisms (SNPs) were mapped to two chromosomal regions, corresponding to three candidate genes. Among them, the candidate genes INPP4B, SCOC, and PABPC4L were identified as being related to the abundance of key microbes. This study provides new insights into the joint contributions of host genetics and probiotics to host growth traits, offering theoretical guidance and data support for the development of efficient and targeted breeding strategies.

Resilience usually refers to the ability of an animal to be minimally affected by disturbance or to quickly return to its pre-disturbance state. Pigs with strong resilience usually have better production performance and higher tolerance to common diseases. This study utilized feed intake records collected by a Feed Intake Recording Equipment from three pig breeds (Duroc: 823; Landrace: 582; and Yorkshire: 2032). Six resilience traits were constructed using the root mean square error (RMSE) of daily feed intake and feeding duration, cumulative feed intake, and cumulative feeding duration derived from ordinary least squares (OLS) regression, along with quantile regression (QR) estimates of daily feed intake and feeding duration. The correlations between these resilience traits and production traits were subsequently estimated. Single-trait genome-wide association studies (GWASs) were performed using imputed resequencing data to identify key genomic regions and candidate genes associated with resilience traits. The estimated heritability ranged from 0.103 to 0.267 for resilience traits and 0.293 to 0.560 for production traits. Moderate genetic correlations were observed among the resilience traits, while moderate to high genetic correlations were found between resilience traits and production traits. In particular, the traits RMSE_FI, RMSE_CFI, QR_FI, and QR_FD exhibited significant moderate to high correlations with most production traits. A genome-wide association study (GWAS) based on imputed whole-genome sequencing data was conducted to identify genomic regions associated with resilience traits in pigs. Using single-trait mixed linear models, 188 SNPs were identified and annotated to 44 candidate genes. Several of these genes (CD74, CSF1R, and HTR4) are involved in host immune responses and signal transduction pathways. These findings contribute to a better understanding of the genetic mechanisms underlying resilience in pigs and provide insights for enhancing genomic selection in pig breeding.

The feeding mode is an important factor affecting the reproductive performance of pigs. The composition and expression of the intestinal microbiota are closely related to the physiological and biochemical indicators of animals. Therefore, to explore the impact of different feeding patterns on the reproductive performance of pigs, this study collected reproductive performance data from 1607 Yorkshire pigs raised under different feeding patterns and conducted a fixed-effect variance analysis. Among them, 731 were in the artificial feeding (AM) group and 876 were in the feeding station feeding (SM) group. Additionally, 40 Yorkshire sows in the late gestation period were randomly selected from each feeding mode for intestinal microbiota analysis. The results of the analysis showed that, in the AM group, both the number of birth deformities (NBD) and the number of stillbirths (NSB) were significantly greater than they were in the SM group (p < 0.05). Additionally, the total number born (TNB) in the AM group was significantly lower than that in the SM group (p < 0.05). The results of the intestinal microbiota analysis revealed that at the phylum level, there were significant differences in nine bacterial taxa between the AM and SM groups (p < 0.05). At the genus level, the abundance of a variety of beneficial bacteria related to reproductive performance in the SM group was significantly greater than that in the AM group. Finally, fecal metabolomic analysis revealed that the contents of butyric acid, isovaleric acid, valeric acid, and isobutyric acid, which are associated with reproductive performance, in the feces of sows in the SM group were significantly higher than those in the AM group (p < 0.05). These results indicate that different feeding methods can affect the gut microbiota composition of Yorkshire pigs and further influence the reproductive performance of pigs through the gut microbiota–metabolic product pathway. The results of this study provide valuable insights for further exploring the relationships between feeding modes, intestinal microbial composition, and host phenotypes.

The number of mummies (MUM) in pigs is a major factor affecting sow reproductive performance. Reducing the incidence of MUM can effectively improve sow utilization efficiency. However, the complex mechanisms by which the host genome, gut microbiome, and metabolome interact to influence sow MUM remain unclear. Based on the current research landscape, this study systematically reveals the regulatory mechanisms of the host genome–gut microbiome-metabolome interaction network on sow MUM. By conducting a multi-omics analysis on the intestinal contents of Yorkshire sows during late gestation across different parities, we constructed a dynamic atlas of the gut microbiota and identified 385 core microbial taxa. Through multi-model MWAS and meta-analysis, we screened six key microbial taxa significantly associated with MUM, including Bacteroidales_RF16_group, Prevotellaceae_Ga6A1_group, Comamonas, Paraprevotella, Dorea, and Gallicola. An mGWAS analysis further identified Bacteroidales_RF16_group as regulated by host genetics, as well as candidate genes such as EGF, ENPEP, and CASP6, and important SNP loci such as rs345237235 and rs3475666995. The study found that the abundance of Proteobacteria in the sow’s gut increased progressively from the first parity, providing a theoretical basis for pathogen suppression mechanisms. By integrating fecal metabolomics data, we constructed a four-dimensional regulatory network of host gene–gut microbiota–metabolite–host phenotype. This study innovatively combines quantitative genetics with multi-omics approaches, not only providing a theoretical foundation for understanding host–microbiota interaction mechanisms but also offering critical scientific guidance for reducing sow MUM incidence and improving reproductive efficiency.