Population Improvement

Abstract

Mass selection was very effective to breed distinct open-pollinated cultivars but not for selecting high-yielding cultivars. Hence, recurrent selection—a population improvement method—was sought to increase the frequency of favorable alleles by selecting the superior individuals in a population, intermating them, and selecting the high-yielding offspring for the next cycle of selection. This repeats until the genetic variation is used up or the target is achieved. Genetic linkage maps in various plants include quantitative trait loci (QTL) causing particular phenotypic effects. Association or linkage disequilibrium mapping, which complements linkage analysis, determines the relations between haplotypes and phenotypes in a population. The whole genome scan or genome-wide association study and candidate gene association are the two association mapping methods. They do not require family or pedigree information and use individuals that may derive from wild species, core germplasm, or breeding subsets such as elite lines and cultivars or synthetic populations. Multi-parent advanced generation recombinant inbred lines provide an ideal resource for dissecting the genetics of QTL using various cultivar backgrounds. DNA markers tracking target traits and spread throughout the genome offer means for incorporating or introgressing many genes or QTL from one or various donors into the recurrent parent; that is, marker-aided breeding. Marker-assisted selection for QTL has, however, a few known impacts in cultivar development of inbreeding species, while the private seed sector has used marker-assisted recurrent selection for breeding populations of outcrossing species. Genome-wide selection (GWS) is an important component of a whole-genome strategy that estimates marker effects of the target population based on training and breeding populations. Selection is made on the breeding population according to genomic-estimated breeding values (GEBV). GWS may increase genetic gain rates by enhancing GEBV accuracy, thus reducing generation intervals and enhancing the use of available plant genetic resources.