Climatic stress is a major limiting factor of production efficiency in beef cattle in tropical and subtropical environments and in dairy cattle throughout most of the world. Use of genomic tools to produce an animal with superior ability for both thermal adaptation and food production represents an energy-efficient sustainable approach to meet the challenge of global climate change. The aim of the project is to identify QTL (Quantitative Trait Loci) associated with regulation of body temperature during heat stress and estimate the accuracy of using these QTL for MAS to improve thermal tolerance. Frequent body temperature measurements, skin temperature and perspiration rate in free ranging cattle will be recorded during heat stress on 2,000 Brangus heifers genotyped with the 250K functional SNP chip. These replacement heifers will be subsequently exposed to synchronized AI and fertility data at first calving will be recorded. Phenomics for thermal tolerance and genomic data will be integrated to identify chromosomal regions associated with regulation of body temperature. We will estimate the accuracy of genomic prediction and define a sufficient reduced SNP set to be used in a MAS program. As expect results, we will have identified SNP and genomic regions associated with thermal tolerance, production and reproduction in crossbred cattle under heat stress.
News published in Agência FAPESP Newsletter about the scholarship: