Improving phenotypic prediction in dairy cattle breeding using the metagenome

Abstract

Ruminants evolved from Artiodactyla in the Eocene 50–70 million years ago. In that period, grass began to populate the largest land surface on Earth. Since then, ruminants and their microbiota have evolved together in symbiosis, creating a very complex natural bioreactor (the rumen) that converts plant material into energy and nutrients that can be utilized by the animal. The complexity of a given microbiota can be expressed as alpha diversity.1 Evolution has created variability in the microbiota composition between species, breeds, and even between individuals. This variability between individuals or niches within individuals can be described in terms of beta diversity,2 and is partially responsible for the efficiency of the animal at feed utilization, as the biochemical reactions and the products and sub-products generated during the degradation of the fibre in the rumen are heterogeneous across different type of microbes. Likewise, the intestines, udder, skin or reproductive apparatus (among other niches) host their particular microbiota. Altogether they shape the cow microbiome and are directly linked to the immune response of the animal, feed digestion, disease susceptibility or fertility. The microbial communities can be characterized using genome approaches through modern sequencing techniques. These allow bioinformaticians to cluster DNA reads into phylogenetic groups up to the species clade. DNA reads can also be clustered into groups of genes with similar function, allowing for a functional analysis rather than taxonomical. The genes that compose the microbiota are called the metagenome. This chapter aims to revisit the state of the art research on the possibilities of predicting complex phenotypes using the metagenome.