Rate of double reduction and genetic variability in yield, quality, and senescence related traits in tetraploid potato (Solanum tuberosum L.)

The amount of genetic variability is the foundation for genetic change in any plant breeding program, and the amount of double reduction can influence genetic gain and the amount of future genetic diversity in polyploid species. Our study investigates these factors using variance components analysis on a dataset comprising 13,131 potato breeding lines and phenotypic data from Scandinavian environments spanning 17 years (2003 to 2021). Pedigree information was used in quantitative genetic models to estimate additive genetic variance and the relative importance of additive and non-additive genetic variance. We used two models, a baseline model (M1) without effects due to specific combining ability (SCA) and M2 (including SCA due to interaction between parental genomes). Two cross-validation (CV) schemes [5-Fold and leave-one-breeding-cycle-out (LBCO)] were used to evaluate the prediction ability (PA) of each model. We estimated the rate of double reduction phenomenon (DRP) by determining the rate best fitting the data using a marginal likelihood approach. Our findings showed a wide range of variation in different traits, with very large proportion of additive genetic variance in dry matter content (DMC), but intermediate additive genetic variance for relative yield (RY), germination (GR), and withering (WNG). All traits showed modest non-additive genetic variance. Furthermore, genotype x environment interaction played a significant role in trait variability but is still much smaller than the additive genetic variance. After using different DRP rates, we found that a model with a 0.05 DRP rate provided the best fit to the data. Heritability estimates indicated a strong genetic basis for DMC, while other traits showed more moderate heritability, which shows contributions from both additive and interaction factors. Model comparison by 5-Fold CV and LBCO and the log likelihood ratio test (LRT) highlighted the importance of considering SCA when capturing trait variability. In 5-Fold CV, PA ranged from 0.296 to 0.812 in M1 and 0.300 to 0.813 in M2. Under LBCO CV, PA ranged from 0.180 to 0.726 in M1 and 0.180 to 0.728 in M2. However, an increase in PA in Model 2, which incorporates SCA, compared to Model 1, can be attributed to the inclusion of SCA effects. Furthermore, the LRT results indicated a highly significant difference between the models. CV and LRT suggest the need for genetic models that account for both additive and SCA effects. Our analysis also showed that genotype x environment interactions should be accounted for in order to maximize the accuracy of predicted breeding values of tetraploid potato clones. The rate of double reductions was small and insignificant.