Abstract
Forest tree breeding has been successful at delivering genetically improved material for multiple traits based on recurrent cycles of selection, mating, and testing. However, long breeding cycles, late flowering, variable juvenile-mature correlations, emerging pests and diseases, climate, and market changes, all pose formidable challenges. Genetic dissection approaches such as quantitative trait mapping and association genetics have been fruitless to effectively drive operational marker-assisted selection (MAS) in forest trees, largely because of the complex multifactorial inheritance of most, if not all traits of interest. The convergence of high-throughput genomics and quantitative genetics has established two new paradigms that are changing contemporary tree breeding dogmas. Genomic selection (GS) uses large number of genome-wide markers to predict complex phenotypes. It has the potential to accelerate breeding cycles, increase selection intensity and improve the accuracy of breeding values. Realized genomic relationships matrices, on the other hand, provide innovations in genetic parameters' estimation and breeding approaches by tracking the variation arising from random Mendelian segregation in pedigrees. In light of a recent flow of promising experimental results, here we briefly review the main concepts, analytical tools and remaining challenges that currently underlie the application of genomics data to tree breeding. With easy and cost-effective genotyping, we are now at the brink of extensive adoption of GS in tree breeding. Areas for future GS research include optimizing strategies for updating prediction models, adding validated functional genomics data to improve prediction accuracy, and integrating genomic and multi-environment data for forecasting the performance of genetic material in untested sites or under changing climate scenarios. The buildup of phenotypic and genome-wide data across large-scale breeding populations and advances in computational prediction of discrete genomic features should also provide opportunities to enhance the application of genomics to tree breeding.
Highlights
Forest tree breeding encompasses a number of steps to increase the frequency of advantageous alleles for several traits concurrently in a target population
To maximize genetic gains per unit time, extensive efforts in tree breeding were devoted to the two fundamental means by which the length of a breeding cycle can be decreased, namely, early selection and accelerated breeding
We focus on the factors that affect and the challenges that remain to fully integrate genomic data in tree breeding in light of the recent promising results of whole-genome prediction
Summary
Forest tree breeding encompasses a number of steps to increase the frequency of advantageous alleles for several traits concurrently in a target population. When considering the practicalities of tree breeding, a number of factors that affect the prospects of GS have to be considered, including the composition of training populations, analytical methods, genotype x environment interaction (G∗E), age-age correlations, the long term models performance and cost and quality of DNA
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