The gut microbiota actually shares the host’s physical space and affects the host’s physiological functions and health indicators through a complex network of interactions with the host. However, its role as a determinant of host health and disease is often underestimated. With the emergence of new technologies including next-generation sequencing (NGS) and advanced techniques such as microbial community sequencing, people have begun to explore the interaction mechanisms between microorganisms and hosts at various omics levels such as genomics, transcriptomics, metabolomics, and proteomics. With the enrichment of multi-omics integrated analysis methods based on the microbiome, an increasing number of complex statistical analysis methods have also been proposed. In this review, we summarized the multi-omics research analysis methods currently used to study the interaction between the microbiome and the host. We analyzed the advantages and limitations of various methods and briefly introduced their application progress.

Litter size has increased and farrowing duration has also prolonged in recent years. The aim of this study was to analyze the effect of litter size and parity on farrowing duration (FAR) to estimate the possibility of selecting a short farrowing duration. We recorded 32,200 parturitions of 8420 Landrace × Yorkshire sows, determined farrowing duration, litter size, parity, gestation length. Results showed that total number of born (TNB) and parity obeyed a cubic (p = 0.0004, p = 0.004) relationship while number born alive (NBA) and number born dead (NBD) obeyed a linear (p = 0.0239, p = 0.0035) relationship with FAR. Gestation length obeyed a linear (p = 0.02) relationship with FAR. FAR of sows with stillbirth was longer than that of sows without stillbirth. Stillbirth rate increased rapidly from about 2% to 4%, especially when FAR was over 240 min. FAR gradually prolonged with the parities. FAR of 7th parity sows was longer than that of 1st~6th parity sows (p < 0.05), but different parity sows had little difference in the same FAR interval except for gilts. Results indicated it was possible and necessary to consider FAR into pig breeding without worrying about decreasing of live litter size or negative effect of parity if FAR was shorter than 300 min.

The development of a comprehensive pig graph pangenome assembly encompassing 27 genomes represents the most extensive collection of pig genomic data to date. Analysis of this pangenome reveals the critical role of structural variations in driving adaptation and defining breed‐specific traits. Notably, the study identifies BTF3 as a key candidate gene governing intramuscular fat deposition and meat quality in pigs. These findings underscore the power of pangenome approaches in uncovering novel genomic features underlying economically important agricultural traits. Collectively, these results demonstrate the value of leveraging large‐scale, multi‐genome analyses for advancing our understanding of livestock genomes and accelerating genetic improvement.

Reproductive traits hold considerable economic importance in pig breeding and production. However, candidate genes underpinning the reproductive traits are still poorly identified. In the present study, we executed a genome-wide association study (GWAS) and runs of homozygosity (ROH) analysis using the PorcineSNP50 BeadChip array for 585 Yorkshire pigs. Results from the GWAS identified two genome-wide significant and eighteen suggestive significant single nucleotide polymorphisms (SNPs) associated with seven reproductive traits. Furthermore, we identified candidate genes, including ELMO1, AOAH, INSIG2, NUP205, LYPLAL1, RPL34, LIPH, RNF7, GRK7, ETV5, FYN, and SLC30A5, which were chosen due to adjoining significant SNPs and their functions in immunity, fertilization, embryonic development, and sperm quality. Several genes were found in ROH islands associated with spermatozoa, development of the fetus, mature eggs, and litter size, including INSL6, TAF4B, E2F7, RTL1, CDKN1C, and GDF9. This study will provide insight into the genetic basis for pig reproductive traits, facilitating reproduction improvement using the marker-based selection methods.

Intestinal microorganisms have been shown to be important factors affecting the growth performance of pigs. Therefore, to investigate the effect of the intestinal microflora structure on the growth performance of pigs, samples from Duroc (n = 10), Landrace (n = 9) and Yorkshire (n = 21) pigs under the same diet and feeding conditions were collected. The fecal microbial composition was profiled via 16S ribosomal RNA (rRNA) gene sequencing. We also analyzed their growth performance. We found that Duroc and Landrace pigs had significant differences in average daily gain (ADG), feed efficiency ratio (FER), growth index (GI), and number of days taken to reach 100 kg (P < 0.05). Moreover, through analysis of the intestinal flora, we also identified 18 species of intestinal flora with significant differences between Duroc and Landrace pigs (P < 0.05). To eliminate the influence of genetic background, the differential intestinal flora of 21 Yorkshire pigs with differences in growth performance was analyzed. The results showed that there were significant correlations between Barnesiella, Dorea, Clostridium and Lactobacillus and pig growth performance. To explore the effect of the intestinal flora on the growth performance of pigs at the molecular level, Lactobacillus, which is the most abundant in the intestine, was selected for isolation and purification and cocultured with intestinal epithelial cells. qPCR was used to determine the effect of Lactobacillus on MC4R gene expression in intestinal epithelial cells. The results showed that Lactobacillus inhibited MC4R gene expression in these cells. The results provide a useful reference for further study of the relationship between the intestinal flora and pig growth performance.