An alternative interpretation of residual feed intake by phenotypic recursive relationships in dairy cattle

Abstract

Genetic evaluation on residual feed intake (RFI) often takes 2 stages. Combining these 2 modeling stages leads to one-step linear regression, eliminating the need to estimate the residuals as the RFI phenotypes specifically. However, fitting phenotypes as regressor variables in a standard linear regression is criticized because phenotypes are subject to measurement errors. Multiple-trait models have been proposed, which give the genetic values of RFI through a follow-up partial regression procedure. By rearranging the linear regression equation, we came across an alternative, causal RFI interpretation by phenotype recursiveness between DMI and energy sinks. In this technical note, we propose a Bayesian recursive structural equation model (RSEM) for directly evaluating RFI, extending its analytical capacity to multiple-trait analysis. Highlights• The model postulates RFI as resulting from phenotypic recursive effects from energy sinks to DMI. • It predicts RFI genetic values and estimates genetic parameters simultaneously.• A simplified algorithm is proposed to sample model parameters via Marko chain Monte Carlo.• The model extends naturally to deal with heterozygous relationships between DMI and energy sinks.• Modeling simultaneous effects between energy sinks and DMI is possible, subject to model identifiability.

Analysis of the causal structure of traits involved in sow lactation feed efficiency

“…We investigated the causal structure among five traits that are involved in LFE and estimated the magnitude of the putative causal effects in this causal structure using data from a population of pigs selected for RFI during growth. The causal structure between components of FE was previously studied by Wu et al [ 15 ] in dairy cattle, but they defined the causal structure by assuming that energy sinks affect FI and that there are no causal relationships between energy sinks. This model means a causal interpretation of RFI by phenotypic recursiveness between FI and energy sinks, which allows the estimation of breeding values and genetic parameters for RFI directly (i.e.…”

“…In the last years, SEM have been increasingly implemented in quantitative genetics, following publication of the paper by Gianola and Sorensen [ 11 ], who adapted these models to this field. Regarding feed efficiency in livestock, to the best of our knowledge, only Abdalla et al [ 14 ] inferred causal structures among feed efficiency traits in a commercial turkey population and only Wu et al [ 15 ] implemented an SEM for FI and energy sinks in dairy cattle, assuming that energy sink traits affect FI and that there is no causal relationship between energy sinks. No studies are available on causal relationships for FE in pigs.…”