Abstract Background Genomic BLUP (GBLUP) can predict breeding values for non-
phenotyped individuals based on the identity-by-state genomic relationship matrix (G). The …

The success and sustainability of a breeding program incorporating genomic information is
largely dependent on the accuracy of predictions. For low heritability traits, large training …

Various models have been used for genomic prediction. Bayesian variable selection models
often predict more accurate genomic breeding values than genomic BLUP (GBLUP), but …

Single-step genomic BLUP (ssGBLUP) model for routine genomic prediction of breeding
values is developed intensively for many dairy cattle populations. Compatibility between the …

Combining purebreed and crossbreed information is beneficial for genetic evaluation of
some livestock species. Genetic evaluations can use relationships based on genomic …

Background A better understanding of the genetic architecture underlying complex traits (eg,
the distribution of causal variants and their effects) may aid in the genomic prediction. Here …

Combining breeds in a multibreed evaluation can have a negative impact on prediction
accuracy, especially if single nucleotide polymorphism (SNP) effects differ among breeds …

Obtaining accurate predictions of unobserved genetic or phenotypic values for complex
traits in animal, plant, and human populations is possible through whole-genome prediction …

Implicit assumption of common (co) variance for all loci in multi-trait Genomic Best Linear
Unbiased Prediction (GBLUP) results in a genomic relationship matrix (G) that is common to …

The weighted single-step genomic best linear unbiased prediction (GBLUP) method has
been proposed to exploit information from genotyped and non-genotyped relatives, allowing …