Quantitative genetic parameters for growth and wood properties in Eucalyptus "urograndis" hybrid using near-infrared phenotyping and genome-wide SNP-based relationships.

A thorough understanding of the heritability, genetic correlations and additive and non-additive variance components of tree growth and wood properties is a requisite for effective tree breeding. This knowledge is essential to maximize genetic gain, that is, the amount of increase in trait performance achieved annually through directional selection. Understanding the genetic attributes of traits targeted by breeding is also important to sustain decade-long genetic progress, that is, the progress made by increasing the average genetic value of the offspring as compared to that of the parental generation.

Improving genomic prediction of growth and wood traits in Eucalyptus using phenotypes from non-genotyped trees by single-step GBLUP.

Genomic Best Linear Unbiased Prediction (GBLUP) in tree breeding typically only uses information from genotyped trees. However, information from phenotyped but non-genotyped trees can also be highly valuable. The single-step GBLUP approach (ssGBLUP) allows genomic prediction to take into account both genotyped and non-genotyped trees simultaneously in a single evaluation.

High-throughput SNP genotyping in the highly heterozygous genome of Eucalyptus: assay success, polymorphism and transferability across species.

Background: High-throughput SNP genotyping has become an essential requirement for molecular breeding and population genomics studies in plant species. Large scale SNP developments have been reported for several mainstream crops. A growing interest now exists to expand the speed and resolution of genetic analysis to outbred species with highly heterozygous genomes.