Single-step genomic prediction of Eucalyptus dunnii using different identity-by-descent and identity-by-state relationship matrices.

ABSTRACT: 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 ABL

SUBMITTER: Jurcic EJ 

PROVIDER: S-EPMC8322403 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature