Integrated multi-tissue transcriptomics reveals cross-tissue regulatory networks and hub genes regulating feed efficiency in aging chicken.

Given the critical impact of feed costs on poultry profitability, it is essential to improve feed efficiency through genetic selection. Although residual feed intake (RFI) serves as the gold-standard metric for feed efficiency assessment, its molecular regulation remains poorly understood. This study estimated the residual feed intake of laying hens from 70 to 100 weeks of age (E-RFI) and estimated the genetic parameters of key production traits (egg quality and feed efficiency) and lipid traits (triglycerides: TG; free fatty acids: FFA; cholesterol: TC). By decoupling the genetic covariance with production traits, we selected 40 extreme E-RFI individuals and performed multiple aspects of transcriptomic analysis across seven tissues (hypothalamus, pituitary, liver, pancreas, duodenum, ileum, and cecum). Key findings revealed moderate heritability of E-RFI (0.45), with production traits showing distinct genetic potential. Egg number (EN70-100w, 0.37) and average egg weight (AEW70-100w, 0.64) for 70 to 100 weeks of age exhibited moderate and high heritability, respectively. Lipid traits displayed low to moderate heritability (TG: 0.01-0.19; FFA: 0.15-0.17; TC: 0.08). Enhanced feed efficiency (reduced E-RFI) correlated with increased egg weight and yolk lipid content but decreased yolk mass and dry matter (DM). Concurrently, hepatic DM (+), FFA (+), and TC (-) levels shifted, while abdominal fat deposition (weight, dry matter, lipids) increased, mirroring yolk lipid dynamics. A total of 22 hub genes (including SHMT1, OAT, CPT1A, and CYCS) were identified associated with E-RFI through multi-tissue integrative analysis, which were specifically enriched in the liver, duodenum, and cecum tissues and exhibited significant cross-tissue functional synergy. These genes constructed a multidimensional regulatory network that influenced feed efficiency through specific molecular interaction mechanisms. Functional analysis revealed that these genes are primarily involved in key biological processes, such as energy metabolism, protein homeostasis regulation, immune signal transduction, and amino acid/lipid metabolism, and regulate growth performance and feed utilization of laying hens through multiple pathways. These findings established a molecular framework for optimizing feed efficiency in aging layers using targeted genetic strategies.