Strategies of preserving genetic diversity while maximizing genetic response from implementing genomic selection in pulse breeding programs

Abstract

Key message Genomic selection maximizes genetic gain by recycling parents to germplasm pool earlier and preserves genetic diversity by restricting the number of fixed alleles and the relationship in pulse breeding programs. Abstract Using a stochastic computer simulation, we investigated the benefit of optimization strategies in the context of genomic selection (GS) for pulse breeding programs. We simulated GS for moderately complex to highly complex traits such as disease resistance, grain weight and grain yield in multiple environments with a high level of genotype-by-environment interaction for grain yield. GS led to higher genetic gain per unit of time and higher genetic diversity loss than phenotypic selection by shortening the breeding cycle time. The genetic gain obtained from selecting the segregating parents early in the breeding cycle (at F1 or F2 stages) was substantially higher than selecting at later stages even though prediction accuracy was moderate. Increasing the number of F1 intercross (F1i) families and keeping the total number of progeny of F1i families constant, we observed a decrease in genetic gain and increase in genetic diversity, whereas increasing the number of progeny per F1i family while keeping a constant number of F1i families increased the rate of genetic gain and had higher genetic diversity loss per unit of time. Adding 50 F2 family phenotypes to the training population increased the accuracy of genomic breeding values (GEBVs) and genetic gain per year and decreased the rate of genetic diversity loss. Genetic diversity could be preserved by applying a strategy that restricted both the percentage of alleles fixed and the average relationship of the group of selected parents to preserve long-term genetic improvement in the pulse breeding program.

Genomic-inferred cross-selection metrics for multi-trait improvement in a recurrent selection breeding program

“…Pea has limited genetic diversity (Yang et al, 2022) and presumably has M e less than the 500 random QTN selected in our study. This aligns with several simulation studies that predominantly assume polygenic traits are controlled by 500 or greater QTN (Wientjes et al, 2015; Yao et al, 2018; Peters et al, 2020; Li et al, 2022; Sabadin et al, 2022).…”

Conservative or non-conservative strategy to advance breeding generation? A case study inEucalyptus benthamiiusing spatial variation and competition model

“…For a constant number of F 1 individuals, increasing the number of F 1 families leads to lower aggregate genetic gain and less loss of genetic variability. The opposite happens when increasing the number of seeds for a constant number of F1 families (Li et al 2022). However, some strategies lead to similar genetic gain with different N e , as the strategies shown in Figure 4, considering the DBH trait.…”

What plant breeding may (and may not) look like in 2050?

“…An alternative breeders are using to maintain high selection intensity is to design recurrent full sib mating schemes (Bassi al., 2016) or to perform GS at more than one segregating filial generation (Li, Kaur, et al, 2022), but both methods require targeted investments. Nevertheless, maintaining high levels of selection intensity in segregating generations is probably the biggest challenge that plant breeders are called to face in the next decades and it is unclear now what innovative solutions will be devised for it by 2050 (da Silva et al, 2021).…”

“…In fact, although increasing the number of markers tested can result in a small increase in accuracy (Zaim et al., 2020), it is by reducing the cost of genotyping one progeny with few hundred markers that breeders will be able to maintain or even increase selection intensity, ultimately achieving higher GG. An alternative breeders are using to maintain high selection intensity is to design recurrent full sib mating schemes (Bassi et al., 2016) or to perform GS at more than one segregating filial generation (Li, Kaur, et al., 2022), but both methods require targeted investments. Nevertheless, maintaining high levels of selection intensity in segregating generations is probably the biggest challenge that plant breeders are called to face in the next decades and it is unclear now what innovative solutions will be devised for it by 2050 (da Silva et al., 2021).…”