The performance of phenomic selection depends on the genetic architecture of the target trait

dc.contributor.authorZhu, Xintian
dc.contributor.authorMaurer, Hans Peter
dc.contributor.authorJenz, Mario
dc.contributor.authorHahn, Volker
dc.contributor.authorRuckelshausen, Arno
dc.contributor.authorLeiser, Willmar L.
dc.contributor.authorWürschum, Tobias
dc.date.accessioned2024-09-03T13:38:03Z
dc.date.available2024-09-03T13:38:03Z
dc.date.issued2021de
dc.description.abstractGenomic selection is a powerful tool to assist breeding of complex traits, but a limitation is the costs required for genotyping. Recently, phenomic selection has been suggested, which uses spectral data instead of molecular markers as predictors. It was shown to be competitive with genomic prediction, as it achieved predictive abilities as high or even higher than its genomic counterpart. The objective of this study was to evaluate the performance of phenomic prediction for triticale and the dependency of the predictive ability on the genetic architecture of the target trait. We found that for traits with a complex genetic architecture, like grain yield, phenomic prediction with NIRS data as predictors achieved high predictive abilities and performed better than genomic prediction. By contrast, for mono- or oligogenic traits, for example, yellow rust, marker-based approaches achieved high predictive abilities, while those of phenomic prediction were very low. Compared with molecular markers, the predictive ability obtained using NIRS data was more robust to varying degrees of genetic relatedness between the training and prediction set. Moreover, for grain yield, smaller training sets were required to achieve a similar predictive ability for phenomic prediction than for genomic prediction. In addition, our results illustrate the potential of using field-based spectral data for phenomic prediction. Overall, our result confirmed phenomic prediction as an efficient approach to improve the selection gain for complex traits in plant breeding.en
dc.identifier.swb1779871880
dc.identifier.urihttps://hohpublica.uni-hohenheim.de/handle/123456789/16503
dc.identifier.urihttps://doi.org/10.1007/s00122-021-03997-7
dc.language.isoengde
dc.rights.licensecc_byde
dc.source1432-2242de
dc.sourceTheoretical and Applied Genetics; Vol. 135, No. 2 (2021), 653-665de
dc.subjectPhenomic prediction
dc.subjectGenomic selection
dc.subjectNear-infrared spectroscopy (NIRS)
dc.subjectTriticale breeding
dc.subjectGenetic architecture
dc.subjectPredictive ability
dc.subject.ddc630
dc.titleThe performance of phenomic selection depends on the genetic architecture of the target traiten
dc.type.diniArticle
dcterms.bibliographicCitationTheoretical and applied genetics, 135 (2021), 2, 653-665. https://doi.org/10.1007/s00122-021-03997-7. ISSN: 1432-2242
dcterms.bibliographicCitation.issn1432-2242
dcterms.bibliographicCitation.issue2
dcterms.bibliographicCitation.journaltitleTheoretical and applied genetics
dcterms.bibliographicCitation.volume135
local.export.bibtex@article{Zhu2021, url = {https://hohpublica.uni-hohenheim.de/handle/123456789/16503}, doi = {10.1007/s00122-021-03997-7}, author = {Zhu, Xintian and Maurer, Hans Peter and Jenz, Mario et al.}, title = {The performance of phenomic selection depends on the genetic architecture of the target trait}, journal = {Theoretical and applied genetics}, year = {2021}, volume = {135}, number = {2}, }
local.export.bibtexAuthorZhu, Xintian and Maurer, Hans Peter and Jenz, Mario et al.
local.export.bibtexKeyZhu2021
local.export.bibtexType@techreport
local.title.fullThe performance of phenomic selection depends on the genetic architecture of the target trait

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