Dissecting the Genetic Architecture of Biofuel-Related Traits in a Sorghum Breeding Population

In this study, we analyzed a breeding population for bioenergy sorghum, which was previously developed based on testcross performance, to compare genomic selection models both trained on and evaluated for the per se performance of the 3rd generation S0 individuals. Of over 200 ancestral inbred accessions in the base population, only 13 founders contributed to the 3rd generation as progenitors. Compared to the founders, the performances of the population per se were improved for target traits. The total genetic variance within the S0 generation progenies themselves for all traits was mainly additive, although non-additive variances contributed to each trait to some extent. For genomic selection, linear regression models explicitly considering all genetic components showed a higher predictive ability than other linear and non-linear models. Although the number and effect distribution of underlying loci was different among the traits, the influence of priors for marker effects was relatively small. These results indicate the importance of considering non-additive effects for dissecting the genetic architecture of early breeding generations and predicting the performance per se.

Source: G3: Genes Genomes Genetics - December 3, 2020 Category: Genetics & Stem Cells Authors: Ishimori, M., Takanashi, H., Hamazaki, K., Atagi, Y., Kajiya-Kanegae, H., Fujimoto, M., Yoneda, J., Tokunaga, T., Tsutsumi, N., Iwata, H. Tags: Genomic Prediction Source Type: research