ABSTRACT:
The use of molecular information in breeding programs contributed to important advances in the improvement of traits of economic interest in livestock production. The advent of single nucleotide polymorphism (SNP) panels applied to genome-wide selection (GWS) and genome-wide association studies (GWAS), along with computational advances (e.g., use of powerful software and robust analyses) allowed a better understanding of the genetic architecture of farm animals and increased the selection efficiency. In this context, the statistic method single-step GBLUP has been frequently used to perform GWS, and more recently GWAS analyses, providing accurate predictions and QTL detection, respectively. Nevertheless, in developing countries, species such as sheep and goats, whose genomic data are more difficult to be obtained, the use of data simulation has been efficient in the study of the major factors involved in the selection process, such as size of training population, density of SNP chips, and genotyping strategies. The effects of these factors are directly associated with the prediction accuracy of genomic breeding values. In this review we showed important aspects of the use of genomics in the genetic improvement of production traits of animals, the main methods currently used for prediction and estimation of molecular marker effects, the importance of data simulation for validation of those methods, as well as the advantages, challenges and limitations of the use of GWS and GWAS in the current scenario of livestock production.
Key words:
genomic breeding values; GWAS; GWS; simulated data; ssGBLUP