Incorporating gene expression and environment for genomic prediction in wheat
Our results show there is a predictive advantage to direct inclusion of the transcriptome for genomic evaluation in wheat breeding for traits where <i>G</i> × <i>E</i> is a factor. However, the complexity and cost of generating transcriptome data are likely to limit its feasibility for commercial breeding at this stage. We demonstrate that combining less costly environmental covariates with conventional genomic data provides a practical alternative with similar gains to the transcriptome when environments are well characterised.
Authors
- Adam Norman (ORCID: https://orcid.org/0000-0002-0794-4907)
- Andrew Gock (ORCID: https://orcid.org/0000-0001-7150-2380)
- Tanya Phongkham
- Shannon Dillon (ORCID: https://orcid.org/0000-0003-2277-9724)
- Eric A. Stone (ORCID: https://orcid.org/0000-0002-2725-4209)
- Kerrie Ramm (ORCID: https://orcid.org/0000-0003-1390-5952)
- Jia Liu (ORCID: https://orcid.org/0000-0001-9206-7576)
- Sandra Stops
- R. F. Eastwood
Institutions
- Australian National University (AU)
- Commonwealth Scientific and Industrial Research Organisation (AU)
- Agriculture and Food (AU)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-05-06
- DOI
- https://doi.org/10.3389/fpls.2025.1506434
- Citations
- 1
- Primary Topic
- Genetics and Plant Breeding
- Type
- article
- Field-Weighted Citation Impact
- 1.75
Funders
- Commonwealth Scientific and Industrial Research Organisation