Background: Hypertrophy, myogenic differentiation, and mass gain of porcine skeletal muscle are key factors in meat production efficiency, regulated by miRNAs through post-transcriptional mechanisms. This study aims to identify miRNA-mRNA pairs linked to growth and muscle development in Jiangquan Black pigs with differing average daily gains (ADGs), providing a foundation for molecular breeding in this breed. Methods: This study divided eight pigs into two groups and analyzed the skeletal muscle characteristics of Jiangquan Black pigs with different average daily weight gains using HE staining. RNA-Seq was conducted to identify differentially expressed miRNAs and mRNAs, Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed, and an integrated miRNA-mRNA regulatory network was subsequently constructed. Results: RNA sequencing analysis identified 255 differentially expressed genes (DEmRNAs, |FC| > 1.5) and 27 differentially expressed miRNAs (DE miRNAs, |FC| > 2). Bioinformatics analysis revealed 330 significantly negatively correlated miRNA-mRNA regulatory pairs, with key pathways, including the MAPK, mTOR, insulin, FoxO, Wnt, and TGF-β signaling pathways, being implicated in muscular development. Quantitative real-time PCR (qRT-PCR) validation confirmed the reliability of the sequencing data. Conclusions: Different ADGs among half-sibling Jiangquan Black pigs with the same diet may be due to the DE miRNAs and DEmRNAs related to skeletal muscle growth and development. These findings reveal the potential regulatory mechanisms of DE miRNAs and DEmRNAs in porcine skeletal muscle growth, providing valuable insights for the next steps in molecular breeding strategies for Jiangquan Black pigs.

DNA methylation plays a pivotal role in the epigenetic regulation of gene expression and holds promise for enhancing livestock meat production. In this study, we analyzed the DNA methylome and transcriptome of the longissimus dorsi muscle (LDM) in Duroc pigs with varying growth rates. Our results reveal that DNA methylation suppressed the expression of key muscle development markers (MYOD, MYOG, MHC1) and proliferation markers (PI67, PCNA), as well as the protein expression and phosphorylation of PI3K and AKT (p < 0.05). Dual-luciferase reporter assays and EMSA showed that SP1 overexpression enhanced the luciferase activity of the wild-type LPAR1 promoter, an effect amplified by the demethylating agent 5-AZA (p < 0.05). The EMSA further demonstrates the relationship between SP1 and the LPAR1 promoter region. Overexpression of SP1 upregulated LPAR1 expression at both the mRNA and protein levels (p < 0.05). Knockdown of LPAR1 reduced muscle marker gene expression and delayed myotube formation, while silencing SP1 disrupted the expression of LPAR1, MEF2C, and MHC1 (p < 0.05), and the demethylation induced by 5-AZA partially reversed these effects. These findings suggest that the DNA methylation/SP1/LPAR1 axis is critical for skeletal muscle growth and development, underscoring the regulatory role of DNA methylation in muscle formation.

To address inefficiencies, pig stress from traditional manual body dimension measurement, and environmental interference in existing automated technologies, this study designed and validated a non-contact measurement system for Jiangquan black pigs based on dual-view (top + side) depth vision (Intel RealSense D455). Key dimensions (body length/width/height, chest depth) were accurately extracted via depth map calibration, dynamic scaling, and U-Net segmentation. Chest girth was estimated using the Ramanujan ellipse perimeter model (MAE = 4.15 cm, R² = 0.908) and integrated as the core parameter for body weight prediction in an empirical formula. This experimental dataset comprises 30 pigs sourced from a single farm, with body weights falling within a limited range (30–100 kg). All dimensions achieved R² > 0.9, with top-view body width performing best (R² = 0.9424, MAE = 1.9 cm). Body weight prediction yielded R² = 0.957 and MAE = 5.1 kg. The system completes measurements in 24 ± 4 s with low hardware costs and stress-free operation, making it suitable for precision breeding in small-to-medium pig farms.