Genomic best linear unbiased prediction (BLUP) is a statistical method that uses relationships between individuals calculated from single-nucleotide polymorphisms (SNPs) to capture relationships at quantitative trait loci (QTL). We show that genomic BLUP exploits not only linkage disequilibrium (LD) and additive-genetic relationships, but also cosegregation to capture relationships at QTL. Simu...

Dr Helen Newton-Turner introduced a powerful model of bringing science into practice by working closely with breeders and the wider industry. This collaboration has led to considerable achievements in genetic improvement Australian animal industries, efficient evaluation systems being implemented, providing platform achieve well defined breeding objectives introduction new technologies such as ...

Prediction of single-cross performance has been a major goal of plant breeders since the beginning of hybrid breeding. Recently, genomic prediction has shown to be a promising approach, but only limited studies have examined the accuracy of predicting single-cross performance. Moreover, no studies have examined the potential of predicting single crosses among random inbreds derived from a serie...

High rates of genetic gain canbe achieved through (1) accurate predictions of breedingvalues (2) high intensities of selection and (3) shorter generation intervals. Reliabilities of ~60% are currently achievable using genomic selection in dairy cattle. This breakthroughmeans that selection of animals can happen at a very early age (i.e. as soon as aDNAsample is available) and has opened opportu...

The European beaver (Castor fiber L.) is an important free-living rodent that inhabits Eurasian temperate forests. Beavers are often referred to as ecosystem engineers because they create or change existing habitats, enhance biodiversity and prepare the environment for diverse plant and animal species. Beavers are protected in most European Union countries, but their genomic background remains ...

BACKGROUND There is wide interest in calculating genomic breeding values (GEBVs) in livestock using dense, genome-wide SNP data. The general framework for genomic selection assumes all individuals are genotyped at high-density, which may not be true in practice. Methods to add additional genotypes for individuals not genotyped at high density have the potential to increase GEBV accuracy with li...

genomic selection is a method to predict the breeding values of individuals using a large number of single nucleotide polymorphism markers. the cost of the high-density marker panel genotyping is very high, which prevents the widely application of genomic selection. the present simulation study was carried out to evaluate the use of low to medium marker density panels to predict direct genomic ...