Quantifying feed efficiency of dairy cattle for genome-wide association analysis

Improving feed efficiency in dairy production is an important endeavor, as it can reduce feed costs and negative impacts of production on the environment. Feed efficiency is a multivariate phenotype that is characterized by a variety of phenotypic variables, such as dry matter intake, body weight gain, and milk yield. Currently, there is no consensus method for quantifying the feed efficiency of lactating dairy cattle for the purpose of breeding selection. Residual feed intake, which is the difference between actual feed intake and predicted intake, has been one of the commonly used measures for feed efficiency. However, such a measure is heterogeneous showing substantial variation in the cow population and has relatively low heritability (0.01~0.38). Hence, its utility in breeding selection is limited. In particular, no prior study has utilized genetic data directly in the development of feed efficiency measures. In this paper, we aim to identify cattle clusters with homogeneous feed efficiency features that are ready to link to genetic variants, and thus can have greater utility in breading selection. In order to achieve this goal, we explore a new multi-view clustering method that jointly analyzes two views of data: phenotypic measures and genotypes, and identifies cattle clusters that are characterized by specific phenotypic features and also associated with genetic markers. Using a set of feed efficiency data collected by USDA, three cattle subgroups have been identified by our analysis, and they offer instructive insights into future feed efficiency studies.