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Genomic selection in hybrid breeding
Author(s) -
Zhao Yusheng,
Mette Michael F.,
Reif Jochen C.
Publication year - 2015
Publication title -
plant breeding
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.583
H-Index - 71
eISSN - 1439-0523
pISSN - 0179-9541
DOI - 10.1111/pbr.12231
Subject(s) - outbreeding depression , biology , genomic selection , selection (genetic algorithm) , relevance (law) , marker assisted selection , heterosis , computational biology , genomics , genome , microbiology and biotechnology , computer science , machine learning , quantitative trait locus , genetics , hybrid , genotype , gene , population , inbreeding , demography , botany , sociology , single nucleotide polymorphism , political science , law
While hybrid breeding is widely applied in outbreeding species, for many self‐pollinating crop plants, it has only recently been established. This may have had its reason in the limitations of methods available for hybrid performance prediction, in particular when established heterotic pools were absent. Genomic selection has been suggested as a promising approach to resolve these limitations. In our review, we briefly introduce the principles of genomic selection as an extension of marker‐assisted selection using genome‐wide high‐density molecular marker data and discuss the advantages and limitations of currently used algorithms. Including the outcome from a recent extended approach to hybrid wheat as a timely example, we summarize current progress in empirical studies on the application of genomic selection for prediction of hybrid performance. Here, we put emphasis on the factors affecting the accuracy of prediction, pointing in particular to the relevance of relatedness, genotype x environment interaction and experimental design. Finally, we discuss future research needs and potential applications.