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

ABSTRACT

KEY MESSAGE Genomic 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. Reciprocal 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 ([Formula see text]), the genetic, GCA and SCA variances ([Formula see text],[Formula see text], [Formula see text]) of the hybrid population, and prediction accuracy ([Formula see text]) 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 [Formula see text] out of 950 candidates in each parent population. Scenarios differed for heritability [Formula see text] and the proportion [Formula see text] of traits, training set (TS) size ([Formula see text]), and maize vs. wheat. Curves of [Formula see text] over selection cycles showed no crossing of both methods. If [Formula see text] was high, [Formula see text] was generally higher for FS-RRGS than HS-RRGS due to higher [Formula see text]. In contrast, HS-RRGS was superior or on par with FS-RRGS, if [Formula see text] or [Formula see text] and [Formula see text] were low. [Formula see text] showed a steeper increase and higher selection limit for scenarios with low [Formula see text], high [Formula see text] and large [Formula see text]. [Formula see text] and even more so [Formula see text] decreased rapidly over cycles for both methods due to the high selection intensity and the role of the Bulmer effect for reducing [Formula see text]. 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.