Transcriptome, proteome and metabolome analysis provide insights on fat deposition and meat quality in pig. (April 2023)

• Record Type: Journal Article
• Authors: Yu, Taiyong; Tian, Xuekai; Li, Dong; He, Yulin; Yang, Peiyu; Cheng, Ye; Zhao, Xin; Sun, Jingchun; Yang, Gongshe
• Is Part Of: Food research international. Volume 166(2023)
• Publication Date: 2023-04
• Subjects: IMF content -- Meat quality -- Multi-omics -- Pig; Food -- Analysis -- Periodicals; Food industry and trade -- Periodicals; Food industry and trade -- Canada -- Periodicals; Food Technology -- Periodicals; Food -- Periodicals; Food-Processing Industry -- Periodicals; Aliments -- Industrie et commerce -- Périodiques; Aliments -- Industrie et commerce -- Canada -- Périodiques; Aliments -- Recherche -- Périodiques; Food industry and trade; Canada; Periodicals; Electronic journals; 664.005
• DOI: 10.1016/j.foodres.2023.112550
• Languages: English
• ISSNs: 0963-9969

Abstract

Graphical abstract: Highlights: There were 12 different fatty acids, 6 different amino acids, 1, 262 differentially expression genes and 140 differentially abundant proteins between QLB pig and LW pig. The blue module had the strongest correlation with IMF content. RapGEF1 may be a key gene that was related to pig IMF content. Abstract: Intramuscular fat (IMF) content, which is an important determinant of meat quality characteristics such as tenderness, juiciness and flavor, has long been a research hotspot. Chinese local pig breeds are famous for their excellent meat quality which is mainly reflected in the high IMF content, strong hydraulic system and et al. However, there are few analysis of meat quality by omics methods. In our study, we identified 12 different fatty acids, 6 different amino acids, 1, 262 differentially expression genes (DEGs), 140 differentially abundant proteins (DAPs) and 169 differentially accumulated metabolites (DAMs) (p < 0.05) with metabolome, transcriptome, and proteome. It has been found that DEGs, DAPs and DAMs were enriched in the Wnt signaling pathway, PI3K-Akt signaling pathway, Rap1 signaling pathway, and Ras signaling pathway which were related to meat quality. Moreover, our Weighted genes co-expression network construction (WGCNA) showed RapGEF1 was the key gene related to IMF content and the RT-qPCR analysis was used to perform validation of the significant genes. In summary, our study provided both fundamental data and new insights to further uncover the secret of pig IMF content.