ArticleGenetics, selection, evolution : GSE2022
Single-step genomic BLUP with genetic groups and automatic adjustment for allele coding.
Article in Genetics, selection, evolution : GSE, 2022. 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.
- Estimation of (co)variance components for very large datasets and complex single-step genomic models.Genetics, selection, evolution : GSE · 2025Article
- Article
- A computationally feasible multi-trait single-step genomic prediction model with trait-specific marker weights.Genetics, selection, evolution : GSE · 2024Article
- Redefining and interpreting genomic relationships of metafounders.Genetics, selection, evolution : GSE · 2024Article
- Heterogeneity in convergence behaviour of the single-step SNP-BLUP model across different effects and animal groups.Genetics, selection, evolution : GSE · 2023Article
- Efficient large-scale single-step evaluations and indirect genomic prediction of genotyped selection candidates.Genetics, selection, evolution : GSE · 2023Article
- Reliabilities of estimated breeding values in models with metafounders.Genetics, selection, evolution : GSE · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
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Abstract
backgroundGenomic estimated breeding values (GEBV) by single-step genomic BLUP (ssGBLUP) are affected by the centering of marker information used. The use of a fixed effect called J factor will lead to GEBV that are unaffected by the centering used. We extended the use of a single J factor to a group of J factors.
resultsJ factor(s) are usually included in mixed model equations (MME) as regression effects but a transformation similar to that regularly used for genetic groups can be applied to obtain a simpler MME, which is sparser than the original MME and does not need computation of the J factors. When the J factor is based on the same structure as the genetic groups, then MME can be transformed such that coefficients for the genetic groups no longer include information from the genomic relationship matrix. We illustrate the use of J factors in the analysis of a Red dairy cattle data set for fertility.
conclusionsThe GEBV from these analyses confirmed the theoretical derivations that show that the resulting GEBV are allele coding independent when a J factor is used. Transformed MME led to faster computing time than the original regression-based MME.
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