Combining genetic gain and diversity by considering average coancestry in clonal selection of Norway spruce

Abstract

 Genetic relationship within a population can be measured by average coancestry. This can also be expressed as an effective number which represents the relative genetic diversity of the population. The goal of breeding can be formulated to maximise genetic value minus average coancestry times a constant (the “penalty constant”). An iterative search algorithm can then be used to find the best selections for meeting this goal. Two such algorithms, one for a fixed number of selections and the other for a variable optimum number, were applied to select a mixture of field-tested Norway spruce clones with known parents. The results were compared with those from the conventional method of restricting parental contributions to the selected population as a means to control diversity. Coancestry-adjusted selection always yielded more gain than restricted selection at a given effective population size (except under circumstances where the methods were equivalent). Expressed another way, at any given level of gain, coancestry-adjusted selection maintained a larger effective population size than did restricted selection. The relative superiority of coancestry-adjusted selection declined when the effective population size approached the lowest value, that at which no penalty or restriction was applied. The method was extended by the second search algorithm to optimise the selected number of clones. The optimal number of clones can be rather large when diversity is heavily valued, but the reduction in genetic gain becomes large.