is an acronym for the multidisciplinary project named
“A BIOINFORMATICS APPROACH TO DAIRY CATTLE BREEDING USING GENOMIC SELECTION”
which is financed by the Science Fund of the Republic of Serbia, as part of the PROMIS programme.
Project Nr.: 6066512
The project started 22th July, 2020 and lasts until 21th July, 2022.
The project budget is: € 169,769.96
This project will consist of a comprehensive multi-level work program. Part of the project is developing statistical theory and gathering new data and knowledge about traits and genes significant for more economical milk production. Another aspect is the construction of practical and directly applicable tools and models that breeders and breeding organization will be able to implement in dairy cattle breeding programs.
The main goals are:
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- forming a database of the pedigree and production information of dairy cattle;
- genotyping of animals to start forming a reference population of dairy cattle in Serbia;
- developing software tools to facilitate the manipulation of this data;
- developing appropriate statistical models and calculating genomic breeding values; and
- educating breeders and experts in breeding organizations to interpret different sources of information.
The pedigree and production data will be collected from breeding organizations evidence that control the productivity of dairy cattle, while the genotyping of the animals will be carried out in an accredited laboratory using appropriate SNP chips. After genotyping, the SNP effects in the reference population and the gBV (genomic breeding value) of candidates for selection will be evaluated using different linear (BLUP — best linear unbiesed prediction) and nonlinear (Bayesian) methods.
Aside from these methods machine learning will be applied to the problem at hand. A neural network will be trained with the collected data from our country and available data from the region. Drawing on new knowledge and technologies in the field of genetics and breeding of domestic animals, in the long term, the project would significantly contribute to the genetic improvement of dairy cattle, but also to the development of research capacity through the application of modern software and statistical and mathematical methods, as well as the use of models obtained through machine learning.
