Prospects for genomic selection in conifer breeding: a simulation study of Cryptomeria japonica

Abstract

Genomic selection (GS) can be a powerful technology in conifer breeding because conifers have long generation intervals, protracted evaluation times, and high costs of breeding inputs. To elucidate the potential of GS for conifer breeding, we simulated 60-year breeding programs in Cryptomeria japonica with and without GS. In conifers, the rapid decay of linkage disequilibrium (LD) can constitute a severe barrier to application of GS. For overcoming that barrier, we proposed an idea to leverage a seed orchard system, which has been used commonly in conifers, because some degree of LD exists in progenies derived from the limited number of elite trees in a seed orchard. The base population used for simulations consisted of progenies from 25 elite trees. Results show that GS breeding (GSB) done without model updating outperformed phenotypic selection breeding (PSB) during the first 30 years, but the genetic gain achieved over the 60 years was smaller in GSB than in PSB. However, GSB with model updating outperformed PSB over the 60 years. The genetic gain achieved over the 60 years of GSB with model updating was nearly twice that of PSB. Advantages of GSB over PSB prevailed, even for a low heritability polygenic trait. The number of markers necessary for efficient GS was a realistic level (e.g., one in every 1 cM), although higher marker density engendered higher accuracy of selection. These results suggest that GS can be useful in C. japonica breeding. Updating of the prediction model was, however, indispensable for attaining the large genetic gain.