| dc.description.abstract | Increase in world population constantly raises the global demand for food. To respond to this demand, livestock systems require to constantly increase their production and/or efficiency. Improvement of beef production can be achieved using genetic and non-genetic strategies, however only with genetic improvement is possible to achieve accumulative improvements across time. Genetic improvement can be achieved by selection or crossbreeding. However, outcomes from both alternatives can be influenced by interactions between genotype and environmental factors, as well as between additive and non-additive genetic components. This study evaluated three different interactions that could be acting on genetic merit predictions and parameter estimations in different cattle populations. First, the interaction between sire and progeny sex was evaluated for pre and post weaning weights and for intramuscular fat in Droughtmaster cattle (Bos indicus-Bos taurus composite breed). Sire by progeny sex interaction was significant for weight at ultrasound measurement (post weaning trait), indicating that it may be possible to achieve different rates of improvement across progeny sex, with intact males having the larger potential for improving this trait. Second, interaction between animals’ additive and non-additive genetic components on birth weight and weaning weight was evaluated across different crossbreed scenarios involving Nellore and Angus influenced parents.
The interaction was significant for both traits; thus, it may be possible to select sires given a specific type of cross, and to improve progeny performance due to achieving a better combined effect between additive and non-additive genetic effects. Third, interaction between animals’ additive genetic component and environments across a gradient of longitude or latitude coordinates within continental United States of America was evaluated for intramuscular fat in Hereford cattle. Results indicated large additive genetic variance and heritability differences across longitude or latitude coordinates, when evaluated at across-regions or within-region levels. Results from this study support that genotype-environment interactions, as well as interaction between additive and non-additive genetic effects could introduce bias in genetic improvement programs if they are not accounted for in prediction equations. Further research is needed to corroborate findings from this study, in addition to further improve modeling strategies for these interactions in genetic prediction models. | en |
