|Lu, Yongfang - Michigan State University|
|Vandehaar, Michael - Michigan State University|
|Spurlock, Diane - Iowa State University|
|Weigel, Kent - University Of Wisconsin|
|Armentano, Lou - University Of Wisconsin|
|Staples, Charlie - University Of Florida|
|Wang, Z - University Of Alberta|
|Coffey, Mike - Collaborator|
|Veerkamp, Roel - Wageningen University|
|De Haas, Yvette - Wageningen University|
|Tempelman, Rob - Michigan State University|
Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/1/2016
Publication Date: 1/1/2017
Citation: Lu, Y., Vandehaar, M.J., Spurlock, D.M., Weigel, K.A., Armentano, L.E., Staples, C.R., Connor, E.E., Wang, Z., Coffey, M., Veerkamp, R.F., De Haas, Y., Tempelman, R.J. 2017. Modeling genetic and non-genetic variation of feed efficiency and its partial relationships between component traits as a function of management and environmental factors. Journal of Dairy Science. 100(1):412-427.
Interpretive Summary: Feed efficiency is determined by partial relationships between feed intake with milk energy and maintenance of metabolic body weight. It was hypothesize that these relationships or partial efficiencies might be heterogeneous across various environmental and management conditions. In addition, both genetic and residual variations in feed efficiency were hypothesized to be similarly heterogeneous. A hierarchical Bayesian multivariate mixed model was therefore proposed to jointly infer upon genetic and residual sources of heterogeneity in partial efficiencies and variation of feed efficiency. The model was validated by simulation and applied to a joint analysis of a dairy feed efficiency consortium dataset containing 5,088 Holstein cows from 13 research stations in Canada, the Netherlands, the United Kingdom, and the United States. Although heterogeneity in genetic and residual partial efficiencies seemed extensive, it generally was not significant. Nevertheless, substantial heterogeneity in genetic and residual variability of feed efficiency was detected at the station, parity, and diet levels. The heritability of feed efficiency ranged from 0.16 to 0.46 across stations, thereby implying that feed efficiency is a more complex trait than what is currently considered in most quantitative genetic analyses. Heterogeneous relationships across environments should be taken into consideration in the genetic characterization and management of feed efficiency in dairy cattle.
Technical Abstract: Feed efficiency (FE), characterized as the ability to convert feed nutrients into saleable milk or meat directly affects the profitability of dairy production, is of increasing economic importance in the dairy industry. We conjecture that FE is a complex trait whose variation and relationships or partial efficiencies (PE) based on DMI conversion to milk energy and metabolic body weight may be highly heterogeneous across environments or management scenarios. In this study, a hierarchical Bayesian multivariate mixed model was proposed to jointly infer upon such heterogeneity at both genetic and non-genetic levels on PE and variance components (VC). The heterogeneity was modeled by embedding mixed effects specifications on PE and VC in addition to those directly specified on traits. We validated the model by simulation and applied it to a joint analysis of a dairy FE consortium dataset with 5,088 Holstein cows from 13 research stations in Canada, the Netherlands, the United Kingdom, and the United States. Although no differences were detected among research stations for PE at the genetic level, there was some evidence of heterogeneity in residual PE. Furthermore, substantial heterogeneity in variance components across stations, parities, and ration were observed with heritability estimates of FE ranging from 0.16 to 0.46 across stations.