Skeletal muscle grows in response to a combination of genetic and environmental factors, and its growth and development influence the quality of pork. Elucidating the molecular mechanisms regulating the growth and development of skeletal muscle is of great significance to both animal husbandry and farm management. The Jiangquan black pig is an excellent pig breed based on the original Yimeng black pig, importing the genes of the Duroc pig for meat traits, and cultivated through years of scientific selection and breeding. In this study, full-length transcriptome sequencing was performed on three growth stages of Jiangquan black pigs, aiming to study the developmental changes in Jiangquan black pigs at different developmental stages at the molecular level and to screen the key genes affecting the growth of skeletal muscle in Jiangquan black pigs. We performed an enrichment analysis of genes showing differential expression and constructed a protein–protein interaction network with the aim of identifying core genes involved in the development of Jiangquan black pigs. Notably, genes such as TNNI2, TMOD4, PLDIM3, MYOZ1, and MYH1 may be potential regulators of muscle development in Jiangquan black pigs. Our results contribute to the understanding of the molecular mechanisms of skeletal muscle development in this pig breed, which will facilitate molecular breeding efforts and the development of pig breeds to meet the needs of the livestock industry.

Objective: The growth of pigs involves multiple regulatory mechanisms, and modern molecular breeding techniques can be used to understand the skeletal muscle growth and development to promote the selection process of pigs. This study aims to explore candidate lncRNAs and mRNAs related to skeletal muscle growth and development among Duroc pigs with different average daily gain (ADG).Methods: A total of 8 pigs were selected and divided into two groups: H group (high-ADG) and L group (low-ADG). And followed by whole transcriptome sequencing to identify differentially expressed (DE) lncRNAs and mRNAs.Results: In RNA-seq, 703 DE mRNAs (263 up-regulated and 440 down-regulated) and 74 DE lncRNAs (45 up-regulated and 29 down-regulated) were identified. In addition, 1,418 Transcription factors (TFs) were found. Compared with mRNAs, lncRNAs had fewer exons, shorter transcript length and open reading frame length. DE mRNAs and DE lncRNAs can form 417 lncRNA-mRNA pairs (antisense, cis and trans). DE mRNAs and target genes of lncRNAs were enriched in cellular processes, biological regulation, and regulation of biological processes. In addition, quantitative trait locus (QTL) analysis was used to detect the functions of DE mRNAs and lncRNAs, the most of DE mRNAs and target genes of lncRNAs were enriched in QTLs related to growth traits and skeletal muscle development. In single-nucleotide polymorphism/insertion-deletion (SNP/INDEL) analysis, 1,081,182 SNP and 131,721 INDEL were found, and transition was more than transversion. Over 60% of percentage were skipped exon events among alternative splicing events.Conclusion: The results showed that different ADG among Duroc pigs with the same diet maybe due to the DE mRNAs and DE lncRNAs related to skeletal muscle growth and development.

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.

Objective: Oxidative stress (OS) is a pathological process arising from the excessive production of free radicals in the body. It has the potential to alter animal gene expression and cause damage to the jejunum. However, there have been few reports of changes in the expression of long noncoding RNAs (lncRNAs) in the jejunum in piglets under OS. The purpose of this research was to examine how lncRNAs in piglet jejunum change under OS.Methods: The abdominal cavities of piglets were injected with diquat (DQ) to produce OS. Raw reads were downloaded from the SRA database. RNA-seq was utilized to study the expression of lncRNAs in piglets under OS. Additionally, six randomly selected lncRNAs were verified using quantitative real-time polymerase chain reaction (qRT‒PCR) to examine the mechanism of oxidative damage.Results: A total of 79 lncRNAs were differentially expressed (DE) in the treatment group compared to the negative control group. The target genes of DE lncRNAs were enriched in gene ontology (GO) terms and Kyoto encyclopedia of genes and genomes (KEGG) signaling pathways. Chemical carcinogenesis-reactive oxygen species, the Foxo signaling pathway, colorectal cancer, and the AMPK signaling pathway were all linked to OS.Conclusion: Our results demonstrated that DQ-induced OS causes differential expression of lncRNAs, laying the groundwork for future research into the processes involved in the jejunum’s response to OS.

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.