Decoding the spatial regulatory architecture of avian adiposity reveals an ADM-centered paracrine relay driven by a selected distal enhancer

Ducks represent an exceptional biological model for studying fat deposition due to their unique metabolic efficiency. However, the genetic "dark matter"—non-coding variants—has long obscured the precise regulatory mechanisms that GWAS alone cannot resolve. In this study, we decoded the regulatory architecture of duck adiposity by integrating epigenomic, 3D genomic, and transcriptomic landscapes across divergent duck lines. By pioneering a "mixed-strategy" gene prioritization—combining WGCNA with a Bayesian framework—we successfully narrowed down millions of variants to 116 high-confidence candidate genes. Most notably, we unmasked a master regulatory switch: a key functional SNP that modulates ADM expression by reshaping chromatin accessibility and enhancer activity, specifically through the recruitment of SMAD2. Relevant evidences indicate that ADM acts as a paracrine signal, driving a cellular "dialogue" that stimulates the proliferation and differentiation of neighboring preadipocytes. This work not only provides a high-resolution map of the duck epigenome but also offers a precision blueprint for genetic selection in poultry breeding.鸭凭借独特的代谢效率，成为研究脂肪沉积的优异生物模型。然而，被称为遗传“暗物质”的非编码变异（non-coding variants）长期以来掩盖了仅靠全基因组关联研究（Genome-Wide Association Study, GWAS）无法解析的精准调控机制。本研究通过整合不同鸭品系的表观基因组、三维基因组与转录组图谱，解析了鸭脂肪沉积的调控架构。本研究首创“混合策略”基因优先级排序方法——将加权基因共表达网络分析（Weighted Gene Co-expression Network Analysis, WGCNA）与贝叶斯框架相结合——成功将数百万个变异筛选至116个高可信度候选基因。尤为重要的是，本研究揭示了一个核心调控开关：一个关键功能性单核苷酸多态性（Single Nucleotide Polymorphism, SNP），可通过重塑染色质开放状态与增强子活性，并通过招募SMAD2蛋白，调控肾上腺髓质素（Adrenomedullin, ADM）的表达。相关研究证据表明，ADM作为一种旁分泌信号分子，介导细胞间“对话”，可刺激邻近前脂肪细胞的增殖与分化。本研究不仅绘制了鸭的高分辨率表观基因组图谱，更为家禽育种中的遗传选育提供了精准蓝图。