Additive and non-additive genetic variance in juvenile Sitka spruce (Picea sitchensis Bong. Carr)

Many quantitative genetic models assume that all genetic variation is additive because of a lack of data with sufficient structure and quality to determine the relative contribution of additive and non-additive variation. Here the fractions of additive (f(a)) and non-additive (f(d)) genetic variation were estimated in Sitka spruce for height, bud burst and pilodyn penetration depth. Approximately 1500 offspring were produced in each of three sib families and clonally replicated across three geographically diverse sites. Genotypes from 1525 offspring from all three families were obtained by RADseq, followed by imputation using 1630 loci segregating in all families and mapped using the newly developed linkage map of Sitka spruce. The analyses employed a new approach for estimating f(a) and f(d), which combined all available genotypic and phenotypic data with spatial modelling for each trait and site. The consensus estimate for f(a) increased with age for height from 0.58 at 2 years to 0.75 at 11 years, with only small overlap in 95% support intervals (I-95). The estimated f(a) for bud burst was 0.83 (I-95=[0.78, 0.90]) and 0.84 (I-95=[0.77, 0.92]) for pilodyn depth. Overall, there was no evidence of family heterogeneity for height or bud burst, or site heterogeneity for pilodyn depth, and no evidence of inbreeding depression associated with genomic homozygosity, expected if dominance variance was the major component of non-additive variance. The results offer no support for the development of sublines for crossing within the species. The models give new opportunities to assess more accurately the scale of non-additive variation.

Automated summary

Many genetic models assume all genetic variation is additive due to lack of data. This research estimates the proportions of additive and non-additive genetic variation in Sitka spruce for height, bud burst, and pilodyn penetration depth. The results show differences in the contribution of additive variation across age groups and locations.