Genetics and breeding of Taurine-Indicine crossbred dairy cattle

This project will contribute to sustainable food production by studying the genetics and breeding of Taurine-Indicine crossbred dairy cattle. Taurine-Indicine crossbred cattle is used in many countries to harness the fitness of Indicine breeds and the productivity of Taurine breeds. This project will focus on the Girolando population that represents 80% of the Brazilian dairy herd.

Foundation for this population is the locally adapted Indicine dairy breed Gyr. Gyr cows are crossed with the productive Taurine dairy breed Holstein. The resulting Girolando cows are repeatedly crossed with the purebred or crossbred bulls. The repeated crossbreeding is causing large variation in adaptability and productivity.

The large variation is both a problem and an opportunity. It is a problem because of inadequate adaptability in low-input environments and inadequate productivity in high-input environments. Both extremes are reducing dairy performance and wasting natural resources.

Even when the mean level of adaptability and productivity match the environment the segregation of Taurine and Indicine genomes is increasing variation beyond the parent breeds. This additional variation is driven by the segregation of additive genetic effects and the interaction of non-additive genetic effects of the two subspecies genomes as well as genome by environment interactions.

This large variation is an opportunity for optimised breeding that would match genetics to the environment and create new improved genome combinations. This project will comprise three work-packages.

The first work-package will analyse genomic data from population genetic perspective to quantify differences between the two sub-species breeds and the genetic composition of crossbreds. This work will make use of recent advances in population genetics to infer whole population trees with recombination across the two subspecies genomes.

The second work-package will expand the population genetic analyses with quantitative genetic analyses of dairy performance under various Brazilian environments and management practices. This will quantify the magnitude of additive and non-additive genetic variation and genotype by environment interaction as well as map this variation to regions of the two subspecies genomes.

The third work-package will leverage the previous work-packages to build a digital twin (modelling / stochastic simulation) breeding programme of the Girolando population and evaluate various breeding strategies in collaboration with stakeholders. The aim will be to develop a strategy for continuous matching and improvement of adaptability and productivity in Brazilian environments. This will use selective breeding and mating strategies based on phenotypic and genomic data.