Southwest Forestry University

Slash pine breeding cycles run more than a decade, so whether genomic selection can speed them depends on how markers are chosen. In 240 slash pine trees, a study confined genome-wide association analysis to each training fold, used association significance to preselect SNPs, and compared eight prediction models across twelve marker densities. Mean prediction ability for growth traits rose from 0.242 with random markers to 0.271 with preselection, an 11.9% gain; wood-quality traits gained 2.2%, oleoresin traits showed no change, and QTN covariates defined by PVE or cross-fold recurrence failed to beat the no-covariate baseline for nine of twelve traits.

Slash pine breeding cycles run more than a decade, so whether genomic selection can speed them depends on how markers are chosen. In 240 slash pine trees, a study confined genome-wide association analysis to each training fold, used association significance to preselect SNPs, and compared eight prediction models across twelve marker densities. Mean prediction ability for growth traits rose from 0.242 with random markers to 0.271 with preselection, an 11.9% gain; wood-quality traits gained 2.2%, oleoresin traits showed no change, and QTN covariates defined by PVE or cross-fold recurrence failed to beat the no-covariate baseline for nine of twelve traits.