Abstract #T305
Section: Breeding and Genetics (posters)
Session: Breeding and Genetics II
Format: Poster
Day/Time: Tuesday 7:30 AM–9:30 AM
Location: Exhibit Hall A
Session: Breeding and Genetics II
Format: Poster
Day/Time: Tuesday 7:30 AM–9:30 AM
Location: Exhibit Hall A
# T305
Genetic and functional relationships among reproductive traits in US Holstein cows.
Fernando Brito1, Guilherme Rosa1, Pablo Pinedo*2, Jose Santos3, Gustavo Schuenemann4, Rodrigo Bicalho5, Ricardo Chebel3, Klibs Galvao3, Robert Gilbert5,9, Sandra Rodriguez-Zas6, Christopher Seabury7, John Fetrow8, William Thatcher3, 1University of Wisconsin, Madison, WI, 2Colorado State University, Fort Collins, CO, 3University of Florida, Gainesville, FL, 4The Ohio State University, Columbus, OH, 5Cornell University, Ithaca, NY, 6University of Illinois, Urbana-Champaign, IL, 7Texas A&M University, College Station, TX, 8University of Minnesota, Saint Paul, MN, 9Ross University, Basseterre, St. Kitts and Nevis, West Indies.
Key Words: causal inference, dairy cattle, reproductive performance
Genetic and functional relationships among reproductive traits in US Holstein cows.
Fernando Brito1, Guilherme Rosa1, Pablo Pinedo*2, Jose Santos3, Gustavo Schuenemann4, Rodrigo Bicalho5, Ricardo Chebel3, Klibs Galvao3, Robert Gilbert5,9, Sandra Rodriguez-Zas6, Christopher Seabury7, John Fetrow8, William Thatcher3, 1University of Wisconsin, Madison, WI, 2Colorado State University, Fort Collins, CO, 3University of Florida, Gainesville, FL, 4The Ohio State University, Columbus, OH, 5Cornell University, Ithaca, NY, 6University of Illinois, Urbana-Champaign, IL, 7Texas A&M University, College Station, TX, 8University of Minnesota, Saint Paul, MN, 9Ross University, Basseterre, St. Kitts and Nevis, West Indies.
Knowledge of causal relationships among phenotypic traits in dairy cattle can contribute to more efficient genetic selection and management decisions. Thus, this research investigated genetic and functional relationships among retained fetal membranes (RP), metritis (MET), clinical endometritis (CE), resumption of cyclicity (CY), pregnancy on d 60 after first AI (P60), and lameness (LS). The data set comprised information on 11,733 Holstein cows from 16 farms located in 4 regions of the US: Northeast (4 herds), Midwest (6 herds), Southeast (1 herd), and Southwest (5 herds). A directed acyclic graph (DAG) describing causal relationships between the traits was inferred using a Bayesian implementation of the Inductive Causation (IC) algorithm. Structural equation models (SEM) were subsequently fitted conditionally on the inferred DAG. Estimates of direct heritability for P60, RP, MET, LS, CE and CY were 0.20 ± 0.07, 0.09 ± 0.02, 0.10 ± 0.04, 0.15 ± 0.03, 0.10 ± 0.03 and 0.35 ± 0.04, respectively, with estimates of genetic correlation among these traits ranging from −0.82 ± 0.07 (MET and CY) to 0.70 ± 0.13 (RP and MET). The IC algorithm retrieved 6 directed relationships: RP- > MET, RP- > CE, LS- > CE, CE- > P60, CY- > P60 and CY- > CE. Except for the directed edge CE- > LS, the signs of the causal relationships were all on the same direction (i.e., same sign) of the corresponding genetic correlations. The inferred DAG indicates that RP and LS are key variables upstream the causal network affecting P60. As such, they should be considered target traits to improve reproductive performance in dairy cattle. The network indicates also that CE is an intermediate variable through which RP and LS affect P60. The moderate magnitude of heritability estimate for P60 suggests that genetic improvement can be obtained through direct selection on P60. Moreover, genetic progress for P60 can be aided by indirect selection on intermediate phenotypes in the network. The causal network provides also information on potential targets for management interventions to improve P60 in dairy herds, such as RP, LS, CE and CY.
Key Words: causal inference, dairy cattle, reproductive performance
