Abstract
Understanding the genetic mechanisms underlying egg production is crucial for improving laying performance in chickens. However, traditional genome-wide association studies (GWAS) have not effectively utilized the information regarding the longitudinal trajectories and dynamics of egg-laying phenotype. In this study, based on individual egg production records over time, we first utilized the Yang-Ning model to characterize four egg production parameters. Our SNP-based GWAS on these parameters, along with three multidimensional GWAS models, captured different aspects of egg-laying dynamics. The novel significant associations and candidate genes identified, including C3, CADPS2, and TLN2, contribute significantly to egg-laying traits. By quantifying both direct and indirect effects of egg production parameters on egg number (EN) through the integration of Bayesian networks and structural equation modeling, we demonstrated that an earlier age at first egg directly promotes EN. The findings from this study enhance our understanding of the genetic mechanisms involved in egg production and provide valuable insights for optimizing chicken breeding strategies.