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Opportunities and challenges from the use of genomic selection for beef cattle breeding in Latin America
- Montaldo, Hugo H., Casas, Eduardo, Ferraz, José Bento Sterman, Vega-Murillo, Vicente E., Román-Ponce, Sergio Iván
- Animal frontiers 2012 v.2 no.1 pp. 23
- DNA, DNA fingerprinting, animal performance, beef cattle, body conformation, breeding value, cattle breeds, cattle production, environment, genes, genetic improvement, genetic markers, genomics, genotype, markets, phenotype, progeny, program evaluation, running, single nucleotide polymorphism, sire evaluation, sires, young animals, Latin America
- Beef cattle production in Latin America is very important worldwide. The region accounts for 29% of the world's cattle population and beef production. Genomics allows the estimation of breeding values for young animals from DNA samples through the use of panels of single nucleotide polymorphisms (a type of DNA genetic marker). This information is used to increase the accuracy of estimated breeding values. More accurate estimates for young animals should increase the rates of improvement for economically important traits. To implement these evaluations, the effects of single nucleotide polymorphisms on the traits need to be estimated in a training population. The cost of running a training population depends on the number and types of measured traits and also on the number of phenotypes and genotypes. Several beef cattle populations in Latin America undergo traditional genetic programs for genetic evaluation. Opportunities exist for increasing the improvement rates by using genomic selection. Not all populations are suitable for short-term implementation of the methodology owing to the small numbers of sires with genetic evaluations and small numbers of progeny per sire. Another short-term consideration is cost, although genotyping costs are decreasing. Longer term reasons to consider using genomic selection are to increase the competitive position of a breed in the market, to select for a larger number of traits more closely related to the economic performance of the animals in specific environments, and to detect the genes associated with variations in productivity so that genetic improvement can become more efficient.