Genomic Selection: A Faster Strategy for Plant Breeding

Many agronomic traits, such as grain yield, are controlled by polygenes with minor effects and epistatic interaction. Genomic selection (GS) uses genome-wide markers to predict a genomic estimate of breeding value (GEBV) that is used to select favorable individuals. GS involves three essential steps: prediction model training, prediction of breeding value, and selection of favorable individual based on the predicted GEBV. Prediction accuracies were evaluated using either correlation between GEBV (predicted) and empirically estimated (observed) value or cross-validation technique. Factors such as marker diversity and density, size and composition of training population, number of QTL, and heritability affect GS accuracies. GS has got potential applications in hybrid breeding, germplasm enhancement, and yield-related breeding programs. Therefore, GS is promising strategy for rapid improvement of genetic gain per unit time for quantitative traits with low heritability in breeding programs