Intramuscular fat (IMF) and visceral adipose tissue (VAT) are both lipids, but have significantly different deposition processes. Furthermore, the heterogeneity of lipid molecular characteristics and mechanisms is unclear. Accordingly, this study used non-targeted lipidomics and transcriptomics to analyze the lipid profiles and metabolism of longissimus dorsi muscle (LDM) and VAT from donkeys. A total of 1,146 and 1,134 lipids belonging to 18 subclasses were identified in LDM and VAT, respectively, with LDM having higher glycerophospholipid (GP) and lower glycerolipid (GL) contents. Polyunsaturated fatty acids (PUFAs) were distributed preferentially at the sn-1 positions in triglycerides (TGs), and sn-2 positions in phosphatidylcholine (PC) and phosphatidylethanolamine (PE). The percentage PUFA content in TGs was significantly lower in LDM than in VAT, while the opposite trend was observed for PUFAs in PC and PE. A total of 110 different lipid molecules (72 downregulated and 38 upregulated) were identified in LDM compared with VAT, of which 11 were considered potential lipid markers. These different lipids were involved in 17 metabolic pathways, including GL and GP metabolisms. Of the 578 differentially expressed genes screened, 311 were downregulated and 267 were upregulated in LDM compared with VAT. Enriched ontology analysis of the differentially expressed genes mainly involved sphingolipid signaling pathways, and GP, GL, and sphingolipid metabolisms. Overall, lipidomics and transcriptomics indicated differences in lipid profiles and metabolism in LDM and VAT, providing new perspectives for the study of heterogeneity in IMF and VAT.

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Lipids are one of the major macronutrients essential for adequate growth and maintenance of human health. Their structure is not only complex but also diverse, which makes systematic and holistic analyses challenging; consequently, little is known regarding the relationship between phenotype and mechanism of action. In recent years, rapid advancements have been made in the fields of lipidomics and bioinformatics. In comparison with traditional approaches, mass spectrometry-based lipidomics can rapidly identify as well as quantify >1,000 lipid species at the same time, facilitating comprehensive, robust analyses of lipids in tissues, cells, and body fluids. Accordingly, lipidomics is now being widely applied in various fields, particularly food and nutrition science. In this review, we discuss lipid classification, extraction techniques, and detection and analysis using lipidomics. We also cover how lipidomics is being used to assess food obtained from livestock and poultry. The information included herein should serve as a reference to determine how to characterize lipids in animal food samples, enhancing our understanding of the application of lipidomics in the field in animal husbandry.