Metabolomic profiling of backfat in Ningxiang pigs reveals lipid dynamics and carcass trait associations during the fattening stage
Abstract
Understanding the metabolic profile of backfat is essential for optimizing breeding strategies and improving pork production. While the early stages of adipose tissue development have been partially characterized, metabolic alterations during the fattening phase (180–360 days)— a critical period for physiological maturation and carcass trait formation—remain insufficiently understood. In this study, we characterized the metabolomic profiles of backfat from Ningxiang pigs across four developmental stages (180d, 240d, 300d, 360d) and evaluated their relationships with carcass traits. A total of 154 metabolites exhibited significant temporal variation (q < 0.05), including functional lipids such as methanandamide phosphate and oleoylethanolamide, which are associated with appetite regulation and lipid metabolism. The progressive accumulation of bioactive exogenous metabolites like α-tocotrienol and cephaeline, indicated potential stage-dependent immunometabolic adaptations. In contrast, several synthetic xenobiotics, potentially derived from feed additives or environmental exposure, accumulated in backfat tissue and may represent potential risks to animal health and pork safety. Co-expression network analysis identified a metabolite module strongly associated (|R| > 0.7, q < 0.05) with key carcass traits, within which psychotrine—an understudied plant-derived alkaloid not previously associated with animal growth— was identified as a hub metabolite. This study establishes a comprehensive metabolic characterization of backfat during the fattening phase in an indigenous pig breed. Collectively, these findings provide novel candidate biomarkers for carcass trait prediction, highlight the potential impact of synthetic compound accumulation, and offer valuable insights for precision breeding, nutritional management, and meat safety assessment in swine production.
Article Details
Authors (15)
Yu Chen
Lihua Cao
Qingming Cui
Yuan Deng
Ji Zhu
Yingying Liu
Institute of Intelligent Machines, Hefei Institutes of Physical Science
Huali Li
Huibo Ren
Xionggui Hu
Xiaogang Zhao
Xinglong He
Huiming Wang
Wenmei Wang
Yinglin Peng
Chen Chen