Abstract
Through stochastic simulations, accuracies of breeding values and response to selection were assessed under traditional pedigree-(BLUP) and genomic-based evaluation methods (GBLUP) in forest tree breeding. The latter provides a methodological foundation for genomic selection. We evaluated the impact of clonal replication in progeny testing on the response to selection realized in seed orchards under variable marker density and target effective population sizes. We found that clonal replication in progeny trials boosted selection accuracy, thus providing additional genetic gains under BLUP. While a similar trend was observed for GBLUP, however, the added gains did not surpass those under BLUP. Therefore, breeding programs deploying extensive progeny testing with clonal propagation might not benefit from the deployment of genomic information. These findings could be helpful in the context of operational breeding programs.
Highlights
Through stochastic simulations, accuracies of breeding values and response to selection were assessed under traditional pedigree-(BLUP) and genomic-based evaluation methods (GBLUP) in forest tree breeding
They expressed the efficiency of GBLUP/best linear unbiased predictions (BLUP) protocols based on the respective ranking of selection candidates and genetic gains provided in forest reproductive material
Building on our earlier stochastic simulations[5], we evaluated the impact of clonal replication in progeny testing on the efficiency of BLUP and GBLUP evaluation and the actual genetic response realized in seed orchards
Summary
Accuracies of breeding values and response to selection were assessed under traditional pedigree-(BLUP) and genomic-based evaluation methods (GBLUP) in forest tree breeding. The latter provides a methodological foundation for genomic selection. When genetic covariance is estimated from DNA markers (e.g., SNP), genomic-based predictions (GBLUP) of true breeding values may provide additional benefits over that of the traditional BLUP, mainly when used in the context of GS. Unlike the studies mentioned above, the genetic response to selection was recently simulated in a seed production population, providing a more realistic basis for comparing actual genetic gains available in forest reproductive material[5] They expressed the efficiency of GBLUP/BLUP protocols based on the respective ranking of selection candidates and genetic gains provided in forest reproductive material. Apart from deploying improved forest reproductive material, one can clonally replicate selection candidates
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