Simulation of marker assisted selection in hybrid populations

Abstract

A computer model is developed that simulates Marker Assisted Selection (MAS) in a population produced by a cross between two inbred lines. Selection is based on an index that incorporates both phenotypic and molecular information. Molecular markers contributing to the index and their relative weights are determined by multiple regression of individual phenotype on the markers. The model is applied to investigate the efficiency of MAS as affected by several factors including total number of markers in the genome, number of markers contributing to the index, population size and heritability of the character. It is demonstrated that selection based on genetic markers can effectively utilize the linkage disequilibrium between genetic markers and QTLs created by crossing inbred lines. Selection is more efficient if markers contributing to the index are re-evaluated each generation than if they are evaluated only once. Increasing the total number of markers in the genome as well as the number of markers contributing to the index does not necessarily result in a higher efficiency of selection. Moreover, too many markers may result in a weaker response to selection. Population size is shown to be the most important factor affecting the efficiency of MAS.