Identification of Characteristic Bioactive Compounds in Silkie Chickens, Their Effects on Meat Quality, and Their Gene Regulatory Network

Abstract

Silkie chicken, an important chicken breed with high medicinal and nutritional value, has a long history of being used as a dietary supplement in China. However, the compounds with health-promoting effects in Silkie chickens remain unclear. In the present study, we conducted a comprehensive analysis of metabolic and lipidomic profiles to identify the characteristic bioactive compounds in Silkie chickens, using a common chicken breed as control. The results showed that the levels of 13 metabolites including estradiol, four lipid subclasses including cardiolipin (CL), eight lipid molecules, and three fatty acids including docosahexaenoic acid (C22:6) were significantly increased in Silkie chickens, which have physiological activities such as resisting chronic diseases and improving cognition. These characteristic bioactive compounds have effects on meat quality characteristics, including improving its water-holding capacity and umami taste and increasing the content of aromatic compounds and phenols. The differentially expressed genes (DEGs) between the two chicken breeds revealed the regulatory network for these characteristic bioactive compounds. Fifteen DEGs, including HSD17B1, are involved in the synthesis of characteristic metabolites. Eleven DEGs, including ELOVL2, were involved in the synthesis and transport of characteristic lipids and fatty acids. In summary, we identified characteristic bioactive compounds in Silkie chickens, and analyzed their effects on meat quality characteristics. This study provided important insight into Silkie chicken meat as a functional food.

Keywords: characteristic lipid; characteristic metabolite; gene regulatory network; meat quality; silkie chicken; volatile flavor compound.

Figure 1

Identification of characteristic bioactive metabolites. (A) Classification and percentage of metabolites in the breast muscle of 30 Silkie chickens and 30 Wuding chickens. (B) PLS-DA based on overall metabolites. (C) Cluster heat map of the differential metabolites. The abscissa represents samples, and the ordinate represents differential metabolites. (D) KEGG pathway enrichment analysis of differential metabolites. Each circle shows a corresponding pathway. Red circles represent significantly upregulated pathways, and blue circles represent significantly downregulated pathways. (E) Characteristic bioactive metabolites and their related metabolic pathways in Silkie chickens.

Figure 2

Identification of characteristic bioactive lipids and fatty acids. (A) PLS-DA based on overall lipid molecules. (B) Distribution of major lipid classes and subclasses. (C) The number of differential lipid molecules in each lipid subclass. Orange and green represent lipid molecules that were significantly upregulated and downregulated in Silkie chickens, respectively. (D) Heat map of differential fatty acids in Silkie and Wuding chickens. Orange, green, and gray squares indicate fatty acids that were significantly upregulated, significantly downregulated, and not differentially expressed in Silkie chickens, respectively. Transparent squares indicate the absence of this fatty acid.

Figure 3

Correlation analysis between characteristic bioactive compounds and meat quality in the breast muscle of Silkie chickens. Red circles represent a significant positive correlation (r > 0.3 and p < 0.05) and blue circles represent a significant negative correlation (r < −0.3 and p < 0.05).

Figure 4

Effects of characteristic bioactive compounds on meat flavor. (A) Classification and percentage of volatile flavor compounds. (B) PLS-DA based on overall volatile flavor compounds. (C) The number of differential volatile flavor compounds in each class. Orange and green represent volatile flavor compounds that were significantly upregulated and downregulated in Silkie chickens, respectively. (D) Correlation analysis of eight upregulated volatiles and characteristic bioactive compounds. Red circles indicate a significant positive correlation (r > 0.4 and p < 0.05).

Figure 5

Statistical analysis of DEGs. (A) Principal component analysis based on overall transcripts. (B) Volcano plot of DEGs in the breast muscle of Silkie and Wuding chickens. (C) GO enrichment analysis and KEGG pathway enrichment analysis of upregulated genes in Silkie chickens.

Figure 6

Identification of key DEGs that regulate characteristic metabolic pathways. Orange represents significantly upregulated metabolites and genes in Silkie chickens, and green represents significantly downregulated metabolites and genes.

Figure 7

Identification of key DEGs that play a role in the biosynthesis of characteristic lipids and fatty acids. Lines indicate a significant positive correlation (r > 0.4 and p < 0.05) between gene expression and the content of lipids and fatty acids.