Claim · model-written summary
In a single environment, metabolomic BLUP (M) exceeded GBLUP prediction accuracy for 10 traits.
- Taxon
- oat
Avena sativat0 - Treatment
- metabolomic BLUP (M)e0
- Outcome
- prediction accuracye0
- Direction
- greatere0
- Value
- 10e0
- Comparator
- GBLUPe0
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleSettingQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“In the single-environment trial, transcriptomic BLUP (T), metabolomic BLUP (M), G + T, G + M, and G + T + M models showed greater prediction accuracy than GBLUP for 5, 10, 11, 17, and 17 traits, respectively, and metabolites generally performed better than transcripts when combined with SNPs.”
t0“oat”
Title
Haixiao Hu; Malachy T. Campbell; Trevor H. Yeats; et al. Theoretical and Applied Genetics 2021. doi:10.1007/s00122-021-03946-4
Other claims from this paper (10)
- Method / resource In a single environment, transcriptomic BLUP (T) exceeded GBLUP prediction accuracy for 5 traits.
- Method / resource In a single environment, G + T exceeded GBLUP prediction accuracy for 11 traits.
- Method / resource In a single environment, G + M exceeded GBLUP prediction accuracy for 17 traits.
- Method / resource In a single environment, G + T + M exceeded GBLUP prediction accuracy for 17 traits.
- Method / resource Metabolites generally outperformed transcripts when combined with SNPs.
- Method / resource Multi-environment multi-trait omics models outperformed counterpart multi-trait GBLUP models.
- Method / resource Multi-environment multi-trait omics models outperformed single-environment omics models.
- Method / resource Unstructured genetic covariance modeling gave the highest prediction accuracy.
- Method / resource Omics-based locus prioritization with a two-kernel model improved prediction in a distantly related oat population.
- Recommendation Authors propose the two-kernel model to improve prediction accuracy for traits with known genetic architecture.