The Huai pig is a well-known indigenous pig breed in China. The main advantages of Huai pigs over Western commercial pig breeds include a high intramuscular fat (IMF) content and good meat quality. There are significant differences in the meat quality traits of the same muscle part or different muscle parts of the same variety. To investigate the potential genetic mechanism underlying the meat quality differences in different pig breeds or muscle groups, longissimus dorsi (LD), psoas major (PM), and biceps femoris (BF) muscle tissues were collected from two pig breeds (Huai and Duroc). There were significant differences in meat quality traits and amino acid content. We assessed the muscle transcriptomic profiles using high-throughput RNA sequencing. The IMF content in the LD, PM, and BF muscles of Huai pigs was significantly higher than that in Duroc pigs (p < 0.05). Similarly, the content of flavor amino acids in the three muscle groups was significantly higher in Huai pigs than that in Duroc pigs (p < 0.05). We identified 175, 110, and 86 differentially expressed genes (DEGs) between the LD, PM, and BF muscles of the Huai and Duroc pigs, respectively. The DEGs of the different pig breeds and muscle regions were significantly enriched in the biological processes and signaling pathways related to muscle fiber type, IMF deposition, lipid metabolism, PPAR signaling, cAMP signaling, amino acid metabolism, and ECM–receptor interaction. Our findings might help improve pork yield by using the obtained DEGs for marker-assisted selection and providing a theoretical reference for evaluating and improving pork quality.

Ovarian development significantly influences the laying performance of geese. In this study, the transcriptome analysis was conducted on the ovarian tissues of Wanxi White Geese during the pre-laying (KL), laying (CL), and ceased-laying period (XL). Short Time-series Expression Miner (STEM) analysis and miRNA–mRNA regulatory network construction were performed to identify the key genes and miRNAs regulating laying traits. Comparative analysis of KL vs. CL, CL vs. XL, and XL vs. KL groups resulted in the identification of 337, 136, and 525 differentially expressed genes (DEGs), and 258, 1131, and 909 differentially expressed miRNAs (DEMs), respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis (p < 0.05) revealed that the main enrichment pathways of DEGs and DEMs at different breeding periods were Neuroactive ligand–receptor interaction, GnRH signaling pathway and Wnt signaling pathway, all associated with ovarian development. According to the three groups of common pathways, four DEGs were screened out, including INHBB, BMP5, PRL, and CGA, along with five DEMs, including let-7-x, miR-124-y, miR-1-y, and miR-10926-z, all of them may affect ovarian development. A miRNA–mRNA regulatory network was constructed through integrated analysis of DEGs and DEMs, revealing nine miRNAs highly associated with ovarian development: miR-101-y, let-7-x, miR-1-x, miR-17-y, miR-103-z, miR-204-x, miR-101-x, miR-301-y, and miR-151-x. The dual-luciferase reporter gene verified the target relationship between WIF1 and miR-204-x, suggesting that these miRNAs may influence ovarian development in Wanxi White Goose by regulating the expression levels of their target genes within ovarian tissue. This study provides a theoretical foundation for analyzing the mechanisms of ovarian development across different breeding periods and accelerating the cultivation of new breeds through post-transcriptional regulation levels.

Background: To explore the important candidate genes and signalling pathways that regulate the laying performance and broodiness behaviour of the Wanxi white goose (WWG). Methods: The bird’s ovarian tissues in laying (CL) and brooding (JL) periods were analysed using transcriptomics. Result: A total of 1,015 differentially expressed genes (DEGs) were detected, with 389 DEGs up-regulated and 626 down-regulated. Gene ontology and KEGG functional results indicated the DEGs were mainly and exhibited marked over-representation across biological processes and signalling pathways related to reproductive hormone secretion, such as reproductive system development, steroid biosynthesis and Aplin signalling pathway. Eight hub genes, including FGF8, FGF18, BDNF, OTX2, FLT3, GRIA1, INSR and IGF1 were found to play an important role in the protein-protein interaction network. The GSEA enrichment analysis significantly correlated ribosome, myocardial contraction and other signalling pathways with the laying performance and broodiness behaviour of WWG. Therefore, these eight hub genes may play a key regulatory function within the synthesis of hormonal secretion as well as follicle maturation within geese. This study provides a theoretical basis for further understanding the regulation mechanism of laying performance in geese.

Background: Laying performance is a key metric for assessing avian reproductive efficiency. The differential gene expression profiles of the Wanxi white goose (WWG) ovarian tissue at different laying stages (pre-oviposition phase, oviposition phase and post-laying phase) were analyzed to mine for candidate genes and signaling pathways related to laying performance. Methods: Ovarian tissue samples were collected from WWG during the pre-oviposition phase (PP), oviposition phase (OP) and post-laying phase (LP) to compare the differentially expressed genes (DEGs) in the ovarian tissues during different oviposition phases. The expression of DEGs and proteins in ovarian tissues at different laying periods was detected by qRT-PCR technology and Western blot technology respectively. Result: A total of 1,701 (PP vs OP), 1,259 (OP vs LP) and 652 (PP vs LP) DEGs were screened and GO and KEGG functional enrichment annotation analysis showed that DEGs were significantly enriched in multiple biological processes and signaling pathways related to the laying performance and follicular development of WWG. These include neuroactive receptor-ligand interaction, ECM-receptor interaction and cytokine-cytokine interaction (p less than 0.05). A DEGs protein-protein interaction network was constructed and five hub genes (ITGB3, VTN, FN1, ITGA2 and VWF) were identified by multi-algorithm analysis using the CytoHubba plug-in. The GSEA enrichment analysis selected signaling pathways related to laying performance and reproductive development of geese (ECM-receptor interaction pathway and Ribosome signaling pathway) (|NES| greater than 1, FDR less than 0.25, p less than 0.05). Five DEGs were randomly selected for fluorescence quantitative PCR (RT-qPCR) verification.