title: Genomic selection: genome-wide prediction in plant improvement.
abstract: Association analysis is used to measure relations between markers and quantitative trait loci (QTL). Their estimation ignores genes with small effects that trigger underpinning quantitative traits. By contrast, genome-wide selection estimates marker effects across the whole genome on the target population based on a prediction model developed in the training population (TP). Whole-genome prediction models estimate all marker effects in all loci and capture small QTL effects. Here, we review several genomic selection (GS) models with respect to both the prediction accuracy and genetic gain from selection. Phenotypic selection or marker-assisted breeding protocols can be replaced by selection, based on whole-genome predictions in which phenotyping updates the model to build up the prediction accuracy.
authors: Department of Plant Breeding, Swedish University of Agricultural Sciences, Sundsvagen 14, Box 101, Alnarp, SE 23053, Sweden.
authors: Zeratsion Abera
authors: ZA
authors: Desta
authors: Department of Plant Breeding, Swedish University of Agricultural Sciences, Sundsvagen 14, Box 101, Alnarp, SE 23053, Sweden. Electronic address: rodomiro.ortiz@slu.se.
authors: Rodomiro
authors: R
authors: Ortiz
mesh_terms: D000383:Agriculture; D001947:Breeding; D018745:Genome, Plant; D010944:Plants / Q000235:genetics*; D012641:Selection, Genetic
keywords: accuracy; breeding cycle; genetic gain; genomic selection; prediction models