Animal breeding, i.e. genetic improvement of livestock, using information on phenotypes and pedigrees, has been very successful. Prediction of future phenotypes using genome wide makers can be used not only for prediction of disease risk and forensics in humans but also in estimation of breeding values for selection of livestock and domesticated crops species. Genomic selection refers to selection decisions based on genomic breeding values (GEBV), where the GEBV for selection candidates are calculated from single nucleotide polymorphism (SNP) markers and a prediction equation. The prediction equation is derived in a large reference population where individuals have both marker and phenotype data. Prediction relies on the assumption that all quantitative trait loci (QTLs) tend to be in strong linkage disequilibrium (LD) with at least one marker and many different statistical models can be applied, including GBLUP, RRBLUP BayesA, BayesB, BayesCpi, and Bayesian Lasso. The accuracy of genomic predictions will depend on the size of reference population, heritability of the trait, the effective population size, density of markers, and the genetic architecture of the complex trait, in particular distribution of loci effects and number of QTLs affecting the trait. Genomic selection can have a major impact on animal breeding programs, especially by providing more accurate estimates for breeding value earlier in the life of breeding animals, giving more selection accuracy and lower generation intervals. In livestock species e.g. sheep, cattle and chicken, over 50000 SNPs that can be genotyped in a single assay are now available. Genomic evaluation has been successfully implemented in the United States, Canada, Great Britain, Ireland, New Zealand, Australia, France, the Netherlands, Germany, and the Scandinavian countries. This review aims primarily to describe the principles, key developments and challenges with genomic prediction, as well as perspectives and its possibility.
