Prediction of Genetic Gains from Selection in Tree Breeding

Abstract

The prediction of genetic gain from artificial selection in a trait is important in plant and animal breeding. Lush’s classical breeder’s equation (BE) is widely used for this purpose, although it is also applied to predicting evolution under natural selection. The current application of high throughput sequencing techniques potentially allows breeders at the individual gene level to capture both additive and non-additive genetic effects. Here, we provide a comprehensive evaluation of predicting genetic gains from the selection at multiple hierarchical levels of population structure (provenances, families within provenances, and individuals within families within provenances). We discuss the processes that could influence the power of prediction under the classical BE, including genetic drift, natural selection, and gene flow. We extend the classical BE to molecular breeding methods for improving the prediction of genetic gains; they include the conventional breeding approach, marker-assistant selection (MAS), genome-wide association study (GWAS), and genomic selection (GS). Lastly, we discuss the genetic gains from the selection using multi-omics traits, including gene expression and epigenetic traits. Our overall synthesis should contribute to a better understanding of predicting genetic gains from the artificial selection under classical and molecular breeding.

Population Structure and Genetic Diversity in the Natural Distribution of Neolamarckia cadamba in China

“…However, the genetic gain from provenance selection could be small, given the extensive pollen flow that effectively reduced population genetic differentiation. Therefore, artificial selection should concentrate on selection from families within provenances, or selection from individuals within families within provenances in breeding [ 72 , 73 ].…”

Unveiling the Complexity of Yield Traits through Genetic Variability, Correlation, and Path Analysis across Diverse Bread Wheat [Triticum aestivum (L.) em. Thell] Germplasm

“…Hence estimation of heritability will give better insights of genetic transmission to next generation compared to variability [20]. Heritability estimates along with genetic advance are more helpful in predicting the gain under selection than heritability estimates alone [21]. However, it is not necessary that a character showing high heritability will always exhibit high genetic advance [22].…”