Recent advancements in genomic technologies have led to the discovery and application of DNA-markers [e.g. single nucleotide polymorphisms (SNPs)] for genetic improvement several aquaculture species. The identification specific regions associated with economically important traits, using, example, genome-wide association studies (GWAS), has allowed incorporation markers linked quantitative trai...

The correct models for quantitative trait locus mapping are the ones that simultaneously include all significant genetic effects. Such models are difficult to handle for high marker density. Improving statistical methods for high-dimensional data appears to have reached a plateau. Alternative approaches must be explored to break the bottleneck of genomic data analysis. The fact that all markers...

Background Prediction of breeding values (BV) using only genotypic information is the final goal of Genomic Selection (GS) [1]. Commonly, BV prediction from traditional BLUP analysis is the input for constructing GS prediction models, and GS predicted BVs are correlated with traditional BLUP BVs to estimate the accuracy of GS models. The use of GS in plant breeding depends on the accuracy of th...

The paper reports on a fast EM algorithm for genomic selection by mapping QTL in genomewide dense SNP marker data. The algorithm called emBayesB was used to analyse a 6000 SNP dataset simulated for the QTLMAS XII workshop. True breeding value was accurately predicted by GEBV with a correlation of 0.85 in the validation data, while the regression coefficient of 0.97 indicated unbiased prediction...