Proceedings, 10th World Congress of Genetics Applied to Livestock Production Searching for Phenotypic Causal Links among Meat Quality Traits in Japanese Black Cattle

Meat quality is one of the most important traits determining carcass price in Japanese beef market. Optimized breeding goals and management practices for improvement of meat quality traits require knowledge regarding potential functional relationships among them and with other economically relevant traits. In this context, the objective of this research was to infer phenotypic causal networks involving beef marbling score (BMS), beef color score (BCS), firmness of beef (FIR), texture of beef (TEX), beef fat color score (BFS), and the ratio of saturated fatty acids to mono unsaturated fatty acids (MUS) from 11,855 fattening Japanese Black cattle. An adaptation of the Inductive Causation (IC) algorithm was implemented to search for causal links among these traits, which was applied to their joint distribution conditionally on genetic effects. Such information was obtained from the posterior distribution of the residual (co)variance matrix of a standard Bayesian multiple trait model. The undirected edges among the traits except for BFS were detected by the IC algorithm with 95% highest posterior density (HPD) intervals. Applying smaller HPD intervals resulted in recovering more edges and the undirected edges were changed into directed ones except between FIR and TEX. The analysis uncovered some interesting functional relationships between these traits, for example indicating that BMS would be affected by interventions on MUS and BCS.