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, genomewide 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 markerassisted breeding protocols can be replaced by selection, based on whole-genome predictions in which phenotyping updates the model to build up the prediction accuracy.

Keywords

accuracy; breeding cycle; genetic gain; genomic selection; prediction models

Published in

Trends in Plant Science
2014, volume: 19, number: 9, pages: 592–601

SLU Authors

• Desta, Zeratsion Abera

  • Department of Plant Breeding, Swedish University of Agricultural Sciences
    

• Ortiz Rios, Rodomiro Octavio

  • Department of Plant Breeding, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Plant Biotechnology
Genetics and Breeding in Agricultural Sciences

Publication identifier

• DOI: https://doi.org/10.1016/j.tplants.2014.05.006

Permanent link to this page (URI)

https://res.slu.se/id/publ/58923