ArticleHeredity2018
A new genomic prediction method with additive-dominance effects in the least-squares framework.
Article in Heredity, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Efficient large-scale genomic prediction in approximate genome-based kernel model.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Genomic prediction of yield-related traits and genome-based establishment of heterotic pattern in maize hybrid breeding of Southwest China.Frontiers in plant science · 2024Article
- A dimensionality-reduction genomic prediction method without direct inverse of the genomic relationship matrix for large genomic data.Plant cell reports · 2023Article
- An efficient genomic prediction method without the direct inverse of the genomic relationship matrix.Frontiers in plant science · 2022Article
- Transcriptome analysis reveals the molecular mechanisms of heterosis on thermal resistance in hybrid abalone.BMC genomics · 2021Article
- Estimating variance components in population scale family trees.PLoS genetics · 2019Article
- Improving Genomic Selection With Quantitative Trait Loci and Nonadditive Effects Revealed by Empirical Evidence in Maize.Frontiers in plant science · 2019Article
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Authors and funding
2 authors.
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Abstract
In our previous work, we proposed a genomic prediction method combing identical-by-state-based Haseman-Elston regression and best linear prediction with additive variance component only (HEBLP|A herein), the most essential component of genetic variation. Since the dominance effects contribute significantly in heterosis, it is desirable to incorporate the HEBLP with dominance variance component that is expected to enhance the predictive accuracy as we move to the further development: HEBLP|AD, a paralleled implementation of genomic prediction compared with genomic best linear unbiased prediction (GBLUP). The simulation results indicated that when the dominance effects contributed to a large proportion of genetic variation, HEBLP|AD and GBLUP|AD, having similar accuracy, both outperformed HEBLP|A; but when the dominance variation was none or little, HEBLP|A, HEBLP|AD, and GBLUP|AD had similar predictability. The analysis of real data from Arabidopsis thaliana F2 population also demonstrated the latter situation. In summary, HEBLP|AD performed stable whether a trait was controlled by dominance effects or not.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.