Prediction accuracy of genomic estimated breeding values for fruit traits in cultivated tomato (Solanum lycopersicum L.).

BACKGROUND: Genomic selection (GS) is an efficient breeding strategy to improve quantitative traits. It is necessary to calculate genomic estimated breeding values (GEBVs) for GS. This study investigated the prediction accuracy of GEBVs for five fruit traits including fruit weight, fruit width, fruit height, pericarp thickness, and Brix. Two tomato germplasm collections (TGC1 and TGC2) were used as training populations, consisting of 162 and 191 accessions, respectively. RESULTS: Large phenotypic variations for the fruit traits were found in these collections and the 51K Axiom™ SNP array generated confident 31,142 SNPs. Prediction accuracy was evaluated using different cross-validation methods, GS models, and marker sets in three training populations (TGC1, TGC2, and combined). For cross-validation, LOOCV was effective as k-fold across traits and training populations. The parametric (RR-BLUP, Bayes A, and Bayesian LASSO) and non-parametric (RKHS, SVM, and random forest) models showed different prediction accuracies (0.594-0.870) between traits and training populations. Of these, random forest was the best model for fruit weight (0.780-0.835), fruit width (0.791-0.865), and pericarp thickness (0.643-0.866). The effect of marker density was trait-dependent and reached a plateau for each trait with 768-12,288 SNPs. Two additional sets of 192 and 96 SNPs from GWAS revealed higher prediction accuracies for the fruit traits compared to the 31,142 SNPs and eight subsets. CONCLUSION: Our study explored several factors to increase the prediction accuracy of GEBVs for fruit traits in tomato. The results can facilitate development of advanced GS strategies with cost-effective marker sets for improving fruit traits as well as other traits. Consequently, GS will be successfully applied to accelerate the tomato breeding process for developing elite cultivars.

Genome-wide association study identifies QTL for eight fruit traits in cultivated tomato (Solanum lycopersicum L.).

Genome-wide association study (GWAS) is effective in identifying favorable alleles for traits of interest with high mapping resolution in crop species. In this study, we conducted GWAS to explore quantitative trait loci (QTL) for eight fruit traits using 162 tomato accessions with diverse genetic backgrounds. The eight traits included fruit weight, fruit width, fruit height, fruit shape index, pericarp thickness, locule number, fruit firmness, and brix. Phenotypic variations of these traits in the tomato collection were evaluated with three replicates in field trials over three years. We filtered 34,550 confident SNPs from the 51 K Axiom® tomato array based on < 10% of missing data and > 5% of minor allele frequency for association analysis. The 162 tomato accessions were divided into seven clusters and their membership coefficients were used to account for population structure along with a kinship matrix. To identify marker-trait associations (MTAs), four phenotypic data sets representing each of three years and combined were independently analyzed in the multilocus mixed model (MLMM). A total of 30 significant MTAs was detected over data sets for eight fruit traits at P < 0.0005. The number of MTA per trait ranged from one (brix) to seven (fruit weight and fruit width). Two SNP markers on chromosomes 1 and 2 were significantly associated with multiple traits, suggesting pleiotropic effects of QTL. Furthermore, 16 of 30 MTAs suggest potential novel QTL for eight fruit traits. These results facilitate genetic dissection of tomato fruit traits and provide a useful resource to develop molecular tools for improving fruit traits via marker-assisted selection and genomic selection in tomato breeding programs.