Genomic selection based on the single-step genomic best linear unbiased prediction (ssGBLUP) approach is becoming an important tool in forest tree breeding. The quality of the variance components and the predictive ability of the estimated breeding values (GEBV) depends on how well marker-based genomic relationships describe the actual genetic relationships at unobserved causal loci. We investigated the performance of GEBV obtained when fitting models with genomic covariance matrices based on two identity-by-descent (IBD) and two identity-by-state (IBS) relationship measures. Multiple-trait multiple-site ssGBLUP models were fitted to diameter and stem straightness in five open-pollinated progeny trials of Eucalyptus dunnii, genotyped using the EUChip60K. We also fitted the conventional ABLUP model with a pedigree-based covariance matrix. Estimated relationships from the IBD estimators displayed consistently lower standard deviations than those from the IBS approaches. Although ssGBLUP based in IBS estimators resulted in higher trait-site heritabilities, the gain in accuracy of the relationships using IBD estimators has resulted in higher predictive ability and lower bias of GEBV, especially for low-heritability trait-site. ssGBLUP based on IBS and IBD approaches performed considerably better than the traditional ABLUP. In summary, our results advocate the use of the ssGBLUP approach jointly with the IBD relationship matrix in open-pollinated forest tree evaluation.

基于单步基因组最佳线性无偏预测（ssGBLUP）方法的基因组选择正在成为林木育种的重要工具。方差分量的质量和估计育种值 (GEBV) 的预测能力取决于基于标记的基因组关系描述未观察到的因果位点的实际遗传关系的程度。我们研究了基于两种血统身份 (IBD) 和两种状态身份 (IBS) 关系度量将模型与基因组协方差矩阵拟合时获得的 GEBV 的性能。在邓尼桉的五次开放授粉后代试验中，使用 EUChip60K 进行基因分型，对多性状多位点 ssGBLUP 模型进行了直径和茎直度的拟合。我们还使用基于谱系的协方差矩阵拟合了传统的 ABLUP 模型。IBD 估计器估计的关系显示出始终低于 IBS 方法的标准差。尽管基于 IBS 估计器的 ssGBLUP 导致了更高的性状位点遗传力，但使用 IBD 估计器的关系准确性的提高导致了 GEBV 的更高的预测能力和更低的偏差，特别是对于低遗传力性状位点。基于 IBS 和 IBD 方法的 ssGBLUP 比传统的 ABLUP 表现要好得多。总之，我们的结果主张在自由授粉林木评估中结合使用 ssGBLUP 方法和 IBD 关系矩阵。