Quantitative Genetics and Genomics Converge to Accelerate Forest Tree Breeding

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.

Potential of Genome-Wide Association Studies and Genomic Selection to Improve Productivity and Quality of Commercial Timber Species in Tropical Rainforest, a Case Study of Shorea platyclados

“…However, due to the long lifespan and juvenility period of forest tree species, evaluation of such conventional breeding is time-consuming, laborious and expensive. Thus, genome-wide approaches, including Genome-Wide Association Study (GWAS) and Genomic Selection (GS), have been recently developed to overcome these problems [7][8][9]. These techniques seem to offer promising strategies for genetic improvement of complex traits and accelerating breeding cycles of forest tree species [7,10,11].…”

Chinese Fir Breeding in the High-Throughput Sequencing Era: Insights from SNPs

“…However, the breeding process has appeared to be slow and still in its infancy compared to many commercial crop and animal species [3]. One major hurdle is the phenotyping need for capturing genetic varieties from a large number of large size candidates at different sites with longtime intervals (e.g., 15 years or more for conifers per breeding cycle) [4][5][6]. Phenotype-inferred causative genetic variation knowledge will definitely continue to be used, but the situation seems to be changing.…”

A 3K Axiom®SNP array from a transcriptome-wide SNP resource sheds new light on the genetic diversity and structure of the iconic subtropical conifer treeAraucaria angustifolia(Bert.) Kuntze

“…The availability of a public, user-friendly 3K SNP array for A. angustifolia and the catalog of 44,318 SNPs predicted to provide ∼29,000 informative SNPs across ∼20,000 loci across the genome, will allow tackling still unsettled questions on its evolutionary history, toward a more comprehensive picture of the origin, past dynamics and future trend of the species’ genetic resources. Additionally, but not less importantly, the SNP array described, unlocks the potential to consider adopting genomic prediction methods [94] to accelerate the still very timid efforts of systematic tree breeding of A. angustifolia, a species with enormous potential for its valuable wood and seed products but with very long generation times. In conclusion, this first fully public fixed content SNP array for A. angustifolia and the additional extensive SNP catalog provided in this work for the future manufacture of even denser arrays, raises this iconic species to a higher level for genetic research, opening opportunities to increase the breadth, precision, long-term portability and impact of the genetic data generated.…”