|Title||Breeding top genotypes and accelerating response to recurrent selection by selecting parents with greater gametic variance|
|Author(s)||Bijma, Piter; Wientjes, Yvonne C.J.; Calus, Mario P.L.|
|Source||Genetics 214 (2020)1. - ISSN 0016-6731 - p. 91 - 107.|
Animal Breeding and Genomics
|Publication type||Refereed Article in a scientific journal|
|Keyword(s)||Gametic breeding value - GEBV - Genomic selection - Mendelian sampling - Response to selection - Usefulness criterion - Virtual gametes - Within-family variation|
Because of variation in linkage phase and heterozygosity among individuals, some individuals produce genetically more variable gametes than others. With the availability of genomic EBVs (GEBVs) or estimates of SNP-effects together with phased genotypes, differences in gametic variability can be quantified by simulating a set of virtual gametes of each selection candidate. Previous results in dairy cattle show that gametic variance can be large. Here, we show that breeders can increase the probability of breeding a top-ranking genotype and response to recurrent selection by selecting parents that produce more variable gametes, using ffiffiffi the index I ¼ GEBV þ p2xpSDgGEBV; where xp is the standardized normal truncation point belonging to selected proportion p, and SDgGEBV is the SD of the GEBV of an individual’s gametes. Benefits of the index were considerably larger in an ongoing selection program with equilibrium genetic parameters than in an initially unselected population. Superiority of the index over selection on GEBV increased strongly with the magnitude of the SDgGEBV; indicating that benefits of the index may vary considerably among populations. Compared to selection on ordinary GEBV, the probability of breeding a top-ranking individual can be increased by ~36%, and response to selection by ~3.6% when selection is strong (P = 0.001) based on values for the Holstein-Friesian dairy cattle population. Two-stage selection, with a preselection on GEBV and a final selection on the index, considerably reduced computational requirements with little loss of benefits. Response to multiple generations of selection and inheritance of the SDgEBV require further study.