Brazilian scientists at São Paulo State University (UNESP) collaborating with colleagues at the University of Maryland and the United States Department of Agriculture (USDA) have developed a dairy cattle breeding method that adds a new parameter to genetic selection and conserves or even improves a population's genetic diversity.
The study, which is published in Journal of Dairy Science, was funded by the São Paulo Research Foundation—FAPESP and USDA.
Value - Milk - Yields - Method - Consideration Besides genetic value associated with milk, fat and protein yields, the new method also takes into consideration the variance in gametic diversity and what the authors call "relative predicted transmitting ability," defined as an individual animal's capacity to transmit its genetic traits to the next generation based on this variance.
"Not all progeny of highly productive animals inherit this quality. The new method selects animals that will produce extremely productive offspring," said Daniel Jordan de Abreu Santos, who conducted the study while he was a postdoctoral fellow at UNESP's School of Agricultural and Veterinary Sciences (FCAV) in Jaboticabal, São Paulo State.
Santos - Research - University - Maryland - United Santos is currently doing more postdoctoral research at the University of Maryland in the United States. This is his second stint at Maryland, where he was previously a research intern with a scholarship from the FAPESP.
"Gamete diversity variance is generated by the separation of homologous chromosomes and the rate of recombination between genes linked to them. It isn't accounted for by the traditional selection method," Santos told.
Method - Probability - Transmission - Traits - Generation The new method estimates the probability of the transmission of traits to the next generation on the basis of the genetic data of a parent or the possible combinations in a given mating.
Although it was developed for the selection of any species, in this study, the method was applied to Holstein and Jersey dairy cattle because of the volume and quality of the available data.