» Articles » PMID: 26566822

Breeding Schemes for the Implementation of Genomic Selection in Wheat (Triticum Spp.)

Overview
Journal Plant Sci
Specialty Biochemistry
Date 2015 Nov 15
PMID 26566822
Citations 114
Authors
Affiliations
Soon will be listed here.
Abstract

In the last decade the breeding technology referred to as 'genomic selection' (GS) has been implemented in a variety of species, with particular success in animal breeding. Recent research shows the potential of GS to reshape wheat breeding. Many authors have concluded that the estimated genetic gain per year applying GS is several times that of conventional breeding. GS is, however, a new technology for wheat breeding and many programs worldwide are still struggling to identify the best strategy for its implementation. This article provides practical guidelines on the key considerations when implementing GS. A review of the existing GS literature for a range of species is provided and used to prime breeder-oriented considerations on the practical applications of GS. Furthermore, this article discusses potential breeding schemes for GS, genotyping considerations, and methods for effective training population design. The components of selection intensity, progress toward inbreeding in half- or full-sibs recurrent schemes, and the generation of selection are also presented.

Citing Articles

Genome-wide association mapping for the identification of stripe rust resistance loci in US hard winter wheat.

Sharma R, Wang M, Chen X, Lakkakula I, Amand P, Bernardo A Theor Appl Genet. 2025; 138(4):67.

PMID: 40063245 PMC: 11893644. DOI: 10.1007/s00122-025-04858-3.


Sparse testing designs for optimizing resource allocation in multi-environment cassava breeding trials.

Lubanga N, Ifie B, Persa R, Dieng I, Rabbi I, Jarquin D Plant Genome. 2025; 18(1):e20558.

PMID: 39912128 PMC: 11800058. DOI: 10.1002/tpg2.20558.


Genomic selection shows improved expected genetic gain over phenotypic selection of agronomic traits in allotetraploid white clover.

Ehoche O, Arojju S, Jahufer M, Jauregui R, Larking A, Cousins G Theor Appl Genet. 2025; 138(1):34.

PMID: 39847157 PMC: 11757872. DOI: 10.1007/s00122-025-04819-w.


Within-family genomic selection in strawberry: Optimization of marker density, trial design, and training set composition.

Sleper J, Tapia R, Lee S, Whitaker V Plant Genome. 2025; 18(1):e20550.

PMID: 39789751 PMC: 11718141. DOI: 10.1002/tpg2.20550.


Enhancing genomic-based forward prediction accuracy in wheat by integrating UAV-derived hyperspectral and environmental data with machine learning under heat-stressed environments.

McBreen J, Babar M, Jarquin D, Ampatzidis Y, Khan N, Kunwar S Plant Genome. 2025; 18(1):e20554.

PMID: 39779660 PMC: 11711122. DOI: 10.1002/tpg2.20554.