APPLICATION OF MULTI-TRAIT BAYESIAN DECISION THEORY FOR PARENTAL GENOMIC SELECTION

In all breeding programs, the decision about which individuals to select and intermate to form the next selection cycle is crucial. The improvement of genetic stocks requires considering multiple traits simultaneously, given that economic value and net genetic merits depend on many traits; therefore, with the advance of computational and statistical tools and genomic selection (GS), researchers are focusing on multi-trait selection. Selection of the best individuals is difficult, especially in traits that are antagonistically correlated, where improvement in one trait might imply a reduction in other(s). There are approaches that facilitate multi-trait selection, and recently a Bayesian decision theory (BDT) has been proposed. Parental selection using BDT has the potential to be effective in multi-trait selection given that it summarizes all relevant quantitative genetic concepts such as heritability, response to selection and the structure of dependence between traits (correlation). In this study, we applied BDT to provide a treatment for the complexity of multi-trait parental selection using three multivariate loss functions (LF), Kullback-Leibler (KL), Energy Score, and Multivariate Asymmetric Loss (MALF), to select the best performing parents for the next breeding cycle in two extensive real wheat data sets. Results show that the high ranking lines in genomic estimated breeding value (GEBV) for certain traits did not always have low values for PEL. For both data sets, the KL loss function gave similar importance to all traits including grain yield. In contrast, the Energy Score and MALF gave better performance in 3 of 4 traits that were different than grain yield. The BDT approach should help breeders to decide based not only on the GEBV per se of the parent to be selected, but also on the level of uncertainty according to the Bayesian paradigm.

KERAGAMAN DAN KEKERABATAN GENETIK GARCINIA BERDASARKAN KANDUNGAN SENYAWA BIOAKTIF DAN AKTIVITAS BIOLOGISNYA: KAJIAN IN SILICO

Garcinia, belongs to the genus Guttiferae, is a very prospective plant for development. Because of apomixis, however, this plant has a narrow genetic diversity. This study aims to determine the genetic diversity and relationships of Garcinia based on the content of bioactive compounds and its biological activities, using in silico approach. A total of 64 Garcinia species were analyzed by a multivariate method using the MVSP ver. 3.1 software. The results showed that based on these characters, Garcinia had a low (narrow) genetic diversity, with a Shannon index of 0.28. However, the xanthone, antifungal activity, and leaf organ are the three of Garcinia characters with a high (wide) genetic diversity. The PCA revealed that these characters are contributed positively to this genetic diversity. The UPGMA analysis also revealed that this germplasm is divide into six main clusters, where the fifth is the largest (53 species). The farthest relationship is shown by G. hanburyi and G. cylindrocarpa, as well as G. bancana and G. excavata, at a coefficient of 0.54. In this case, G. mangostana, the most popular species of Garcinia, has the closest relationship with G. wightii at a coefficient of 0.87, and fartest to G. cylindrocarpa. This information might be valuable in supporting the preservation and breeding programs of Garcinia in Indonesia, particularly for parental selection in the development of superior cultivars.

Identification of superior parental lines for biparental crossing via genomic prediction

A parental selection approach based on genomic prediction has been developed to help plant breeders identify a set of superior parental lines from a candidate population before conducting field trials. A classical parental selection approach based on genomic prediction usually involves truncation selection, i.e., selecting the top fraction of accessions on the basis of their genomic estimated breeding values (GEBVs). However, truncation selection inevitably results in the loss of genomic diversity during the breeding process. To preserve genomic diversity, the selection of closely related accessions should be avoided during parental selection. We thus propose a new index to quantify the genomic diversity for a set of candidate accessions, and analyze two real rice (Oryza sativa L.) genome datasets to compare several selection strategies. Our results showed that the pure truncation selection strategy produced the best starting breeding value but the least genomic diversity in the base population, leading to less genetic gain. On the other hand, strategies that considered only genomic diversity resulted in greater genomic diversity but less favorable starting breeding values, leading to more genetic gain but unsatisfactorily performing recombination inbred lines (RILs) in progeny populations. Among all strategies investigated in this study, compromised strategies, which considered both GEBVs and genomic diversity, produced the best or second-best performing RILs mainly because these strategies balance the starting breeding value with the maintenance of genomic diversity.

Identify Superior Parental Lines for Biparental Crossing via Genomic Prediction: Rice as an Example

Background A set of superior parental lines is the key to high-performing recombinant inbred lines (RILs) for biparental crossing in a rice breeding program. The number of possible crosses in such a breeding program is often far greater than the number that breeders can handle in the field. A practical parental selection method via genomic prediction (GP) is therefore developed to help breeders identify a set of superior parental lines from a candidate population before field trials. Results The parental selection via GP often involves truncation selection, selecting the top fraction of accessions based on their genomic estimated breeding values (GEBVs). However, the truncation selection inevitably causes a loss of genomic diversity in the breeding population. To preserve genomic variation, the selection of closely related accessions should be avoided. We first proposed a new index to quantify the genomic diversity for a set of candidate accessions. Then, we compared the performance of three classes of strategy for the parental selection, including those consider (a) GEBV only, (b) genomic diversity only, and (c) both GEBV and genomic diversity. We analyzed two rice (Oryza sativa L.) genome datasets for the comparison. The results show that the strategies considering both GEBV and genomic diversity have the best or second-best performance for all the traits analyzed in this study. Conclusion Combining GP with Monte Carlo simulation can be a useful means of parental selection for rice pre-breeding programs. Different strategies can be implemented to identify a set of superior parental lines from a candidate population. In consequence, the strategies considering both GEBV and genomic diversity that can balance the starting GEBV average with maintenance of genomic diversity should be recommended for practical use.

Preservation of Genetic Variation in a Breeding Population for Long-Term Genetic Gain

Genomic selection has been successfully implemented in plant and animal breeding. The transition of parental selection based on phenotypic characteristics to genomic selection (GS) has reduced breeding time and cost while accelerating the rate of genetic progression. Although breeding methods have been adapted to include genomic selection, parental selection often involves truncation selection, selecting the individuals with the highest genomic estimated breeding values (GEBVs) in the hope that favorable properties will be passed to their offspring. This ensures genetic progression and delivers offspring with high genetic values. However, several favorable quantitative trait loci (QTL) alleles risk being eliminated from the breeding population during breeding. We show that this could reduce the mean genetic value that the breeding population could reach in the long term with up to 40%. In this paper, by means of a simulation study, we propose a new method for parental mating that is able to preserve the genetic variation in the breeding population, preventing premature convergence of the genetic values to a local optimum, thus maximizing the genetic values in the long term. We do not only prevent the fixation of several unfavorable QTL alleles, but also demonstrate that the genetic values can be increased by up to 15 percentage points compared with truncation selection.

Parental Empowerment, Involvement, and Satisfaction: A Comparison of Choosers of Charter, Catholic, Christian, and District-Run Public Schools

Purpose: This study investigates parental empowerment, involvement, and satisfaction in charter, Catholic, Christian, and district-run public schools. The analyses of these indicators across school types also differentiate parents who chose district-run public schools through residential selection from those who did not. Research Design: A survey of 1,699 parents residing in Indiana was linked to school-level administrative data for the analyses. Parents in schools of choice were first compared with parents in district-run public schools using controls for demographic, school, and geographic characteristics. Parents in schools of choice were then compared with parents who chose district-run public schools through residential selection. Findings: Patterns were largely consistent with charter, Christian, and Catholic schools exhibiting greater parental empowerment, involvement, and satisfaction relative to district-run public schools. However, when parents in these schools of choice were compared with parents who chose district-run public schools through residential selection, these differences decreased. Strong negative relationships with parental empowerment, involvement, and satisfaction were observed for parents who did not choose district-run public schools through residential selection. Conclusions: This study highlights the importance of parental selection into district-run public schools through choice of residence—a typically unobserved form of school selection in the literature. In district-run public schools, results suggest that deliberate strategies may be needed to support nonchoosers. Findings also indicate a need for future research on possible approaches that leaders use in different school types that contribute to greater parental empowerment, involvement, and satisfaction.