Genomic prediction in hybrid breeding: II. Reciprocal recurrent genomic selection with full-sib and half-sib families

Abstract

AbstractKey messageGenomic prediction of GCA effects based on model training with full-sib rather than half-sib families yields higher short- and long-term selection gain in reciprocal recurrent genomic selection for hybrid breeding, if SCA effects are important.AbstractReciprocal recurrent genomic selection (RRGS) is a powerful tool for ensuring sustainable selection progress in hybrid breeding. For training the statistical model, one can use half-sib (HS) or full-sib (FS) families produced by inter-population crosses of candidates from the two parent populations. Our objective was to compare HS-RRGS and FS-RRGS for the cumulative selection gain ($$\Sigma \Delta G$$ΣΔG), the genetic, GCA and SCA variances ($$\sigma_{G}^{2}$$σG2,$$\sigma_{gca}^{2}$$σgca2,$$\sigma_{sca}^{2}$$σsca2) of the hybrid population, and prediction accuracy ($$r_{gca}$$rgca) for GCA effects across cycles. Using SNP data from maize and wheat, we simulated RRGS programs over 10 cycles, each consisting of four sub-cycles with genomic selection of$$N_{e} = 20$$Ne=20out of 950 candidates in each parent population. Scenarios differed for heritability$$\left( {h^{2} } \right)$$h2and the proportion$$\tau = 100 \times \sigma_{sca}^{2} :\sigma_{G}^{2}$$τ=100×σsca2:σG2of traits, training set (TS) size ($$N_{TS}$$NTS), and maize vs. wheat. Curves of$$\Sigma \Delta G$$ΣΔGover selection cycles showed no crossing of both methods. If$$\tau$$τwas high,$$\Sigma \Delta G$$ΣΔGwas generally higher for FS-RRGS than HS-RRGS due to higher$$r_{gca}$$rgca. In contrast, HS-RRGS was superior or on par with FS-RRGS, if$$\tau$$τor$$h^{2}$$h2and$$N_{TS}$$NTSwere low.$$\Sigma \Delta G$$ΣΔGshowed a steeper increase and higher selection limit for scenarios with low$$\tau$$τ, high$$h^{2}$$h2and large$$N_{TS}$$NTS.$$\sigma_{gca}^{2}$$σgca2and even more so$$\sigma_{sca}^{2}$$σsca2decreased rapidly over cycles for both methods due to the high selection intensity and the role of the Bulmer effect for reducing$$\sigma_{gca}^{2}$$σgca2. Since the TS for FS-RRGS can additionally be used for hybrid prediction, we recommend this method for achieving simultaneously the two major goals in hybrid breeding: population improvement and cultivar development.