Economical optimization of a breeding scheme by selective phenotyping of the calibration set in a multi-trait context: application to bread making quality.

KEY MESSAGE: Trait-assisted genomic prediction approach is a way to improve genetic gain by cost unit, by reducing budget allocated to phenotyping or by increasing the program's size for the same budget. This study compares different strategies of genomic prediction to optimize resource allocation in breeding schemes by using information from cheaper correlated traits to predict a more expensive trait of interest. We used bread wheat baking score (BMS) calculated for French registration as a case study. To conduct this project, 398 lines from a public breeding program were genotyped and phenotyped for BMS and correlated traits in 11 locations in France between 2000 and 2016. Single-trait (ST), multi-trait (MT) and trait-assisted (TA) strategies were compared in terms of predictive ability and cost. In MT and TA strategies, information from dough strength (W), a cheaper trait correlated with BMS (r = 0.45), was evaluated in the training population or in both the training and the validation sets, respectively. TA models allowed to reduce the budget allocated to phenotyping by up to 65% while maintaining the predictive ability of BMS. TA models also improved the predictive ability of BMS compared to ST models for a fixed budget (maximum gain: + 0.14 in cross-validation and + 0.21 in forward prediction). We also demonstrated that the budget can be further reduced by approximately one fourth while maintaining the same predictive ability by reducing the number of phenotypic records to estimate BMS adjusted means. In addition, we showed that the choice of the lines to be phenotyped can be optimized to minimize cost or maximize predictive ability. To do so, we extended the mean of the generalized coefficient of determination (CDmean) criterion to the multi-trait context (CDmulti).

Linkage disequilibrium in synthetic varieties of perennial ryegrass.

Synthetic varieties obtained after three to four panmictic generations are variable, not structured and so can be used for association studies. The pattern of linkage disequilibrium (LD) decay determines whether a genome scan or a candidate gene approach can be used for an association study between genotype and phenotype. Our goal was to evaluate the effect of the number of parents used to build the synthetic varieties on the pattern of LD decay. LD was investigated in the gibberelic acid insensitive gene (GAI) region in three synthetic varieties of perennial ryegrass (Lolium perenne L.) chosen for their contrasted number of parents in the initial polycrosses. Results were compared with those obtained from a core collection. STS and SSR markers were used to evaluate variation, structuration and LD in each variety. As expected, the varieties variability increased with the number of parents almost up to the core collection variability. No structuration was observed in the varieties. Significant LDs were observed up to 1.6 Mb in a variety originated from six related parents and not above 174 kb in a variety originated from 336 parents. These results suggest that a candidate gene approach can be used when varieties have a large number of parents and a genome scan approach can be envisaged in specific regions when varieties have a low number of parents. Nevertheless, we strongly recommend to estimate the pattern of LD decay in the population and in the genomic region studied before performing an association study.