From long-term progeny trials to genomic selection: empirical prediction and simulation-guided redesign of Scots pine breeding in Germany

Abstract

Long breeding cycles constrain genetic gain in Scots pine, while mature progeny trials can provide reference populations for genomic selection. We combined phenotypic records from two German trials established in 1990 with dense SNP data. We complemented these data with an offspring-level parentage audit, duplicate filtering, and simulations of breeding strategies. Of 1,986 phenotype-matched genotyped trees, 1,668 formed the parentage-green set and 1,651 remained after exclusion of 17 near-duplicate samples. The final population comprised 1,521 supported controlled-cross offspring and 130 mother-known, father-unknown offspring from 87 progeny labels. Across 14 trait-by-age measurements, GBLUP gave the clearest improvements for diameter and volume from age 20 onwards, whereas height was more mixed. At age 35, ABLUP versus GBLUP heritability was 0.155 versus 0.235 for diameter, 0.265 versus 0.263 for height, and 0.172 versus 0.236 for volume. Leave-progeny-out predictive ability increased from 0.205 to 0.238, 0.249 to 0.265, and 0.203 to 0.239, respectively. SNPscan_breeder simulations compared phenotypic selection, progeny testing, cross-generation genomic selection, and genomic selection with phenotypic thinning under five diversity variants. Progeny testing produced the greatest cumulative gain, but its 45-year cycle reduced annual response. Under the base assumptions, genomic selection with phenotypic thinning gave the highest annual gains for height and fungal resistance, whereas pure genomic selection gave the highest annual diameter gain. Genomic strategies accumulated more kinship than conventional strategies, although a {lambda} = 0.10 kinship penalty improved founder retention with little loss of gain; no mitigation option simultaneously maximised gain, prediction accuracy, and diversity. These results support genomic shortlisting within a field-tested programme with explicit reference-population updating and diversity management.