Genomic selection is an upgrading form of marker-assisted selection for quantitative traits, and it differs from the traditional marker-assisted selection in that markers in the entire genome are used to predict genetic values and the QTL detection step is skipped. Genomic selection holds the promise to be more efficient than the traditional marker-assisted selection for traits controlled by po...

The change from a Mendelian to a genomic breeding paradigm poses three challenges: to map the components of animal breeding onto a genomic conceptual frame work; to show how the genetic parameters comprising a genomic analysis can be obtained from actual farm data; and to show how genomic parameters can guide a breeding program. We are currently heavily engaged in the second challenge, but shou...

BACKGROUND The simulated dataset of the 13th QTL-MAS workshop was analysed to i) detect QTL and ii) predict breeding values for animals without phenotypic information. Several parameterisations considering all SNP simultaneously were applied using Gibbs sampling. RESULTS Fourteen QTL were detected at the different time points. Correlations between estimated breeding values were high between m...

BACKGROUND Bayesian approaches for predicting genomic breeding values (GEBV) have been proposed that allow for different variances for individual markers resulting in a shrinkage procedure that uses prior information to coerce negligible effects towards zero. These approaches have generally assumed application to high-density genotype data on all individuals, which may not be the case in practi...

BACKGROUND Bayesian methods allow prediction of genomic breeding values (GEBVs) using high-density single nucleotide polymorphisms (SNPs) covering the whole genome with effective shrinkage of SNP effects using appropriate priors. In this study we applied a modification of the well-known BayesA and BayesB methods to estimate the proportion of SNPs with zero effects (π) and a common variance for ...

Genomic selection using high-density SNP panels was first implemented in dairy cattle breeding programs. It provided benefits in terms of reduced generation intervals, improved accuracies of selecting young animals, and reductions in costs associated with the requirement of progeny testing bulls in traditional breeding programs (Hayes et al., 2009). Several distinct features of the poultry bree...

OBJECTIVE Holsteins are known as the world's highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein) using Korean Holstein data. METHODS This study was performed using single nucleotide polymorphism (SNP) chip data (Illumina BovineSNP50 Beadchip) of 911 Korean Holstein individuals. ...

BACKGROUND The goal of this study was to apply Bayesian and GBLUP methods to predict genomic breeding values (GEBV), map QTL positions and explore the genetic architecture of the trait simulated for the 15th QTL-MAS workshop. METHODS Three methods with models considering dominance and epistasis inheritances were used to fit the data: (i) BayesB with a proportion π = 0.995 of SNPs assumed to h...

Genomic selection (GS) is a promising strategy for enhancing genetic gain. We investigated the accuracy of genomic estimated breeding values (GEBV) in four inter-related synthetic populations that underwent several cycles of recurrent selection in an upland rice-breeding program. A total of 343 S2:4 lines extracted from those populations were phenotyped for flowering time, plant height, grain y...