Twelve Years into Genomic Selection in Forest Trees: Climbing the Slope of Enlightenment of Marker Assisted Tree Breeding

• Published in: Forests Vol. 13; no. 10; p. 1554
• Main Author: Grattapaglia, Dario
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.10.2022
• Subjects: Animal breeding; Brazil; Breeding methods; Empirical analysis; Environmental aspects; forest tree breeding; Forests; Forests and forestry; Gene sequencing; Genetic aspects; Genetic improvement; Genetic markers; Genetics; genomic selection; Genomics; Genotyping; MAS; Methods; New technology; Nucleotides; Phenotypes; Physiological aspects; Pine needles; Plant breeding; Polygenic inheritance; Polymorphism; Productivity; Quantitative genetics; Single-nucleotide polymorphism; SNPs; Trees; Whole genome sequencing; Brazil
• ISSN: 1999-4907; 1999-4907
• DOI: 10.3390/f13101554

Twelve years have passed since the early outlooks of applying genomic selection (GS) to forest tree breeding, initially based on deterministic simulations, soon followed by empirical reports. Given its solid projections for causing a paradigm shift in tree breeding practice in the years to come, GS went from a hot, somewhat hyped, topic to a fast-moving area of applied research and operational implementation worldwide. The hype cycle curve of emerging technologies introduced by Gartner Inc. in 1995, models the path a technology takes in terms of expectations of its value through time. Starting with a sudden and excessively positive “peak of inflated expectations” at its introduction, a technology that survives the “valley of disappointment” moves into maturity to climb the “slope of enlightenment”, to eventually reach the “plateau of productivity”. Following the pioneering steps of GS in animal breeding, we have surpassed the initial phases of the Gartner hype cycle and we are now climbing the slope of enlightenment towards a wide application of GS in forest tree breeding. By merging modern high-throughput DNA typing, time-proven quantitative genetics and mixed-model analysis, GS moved the focus away from the questionable concept of dissecting a complex, polygenic trait in its individual components for breeding advancement. Instead of trying to find the needle in a haystack, i.e., the “magic” gene in the complex and fluid genome, GS more efficiently and humbly “buys the whole haystack” of genomic effects to predict complex phenotypes, similarly to an exchange-traded fund that more efficiently “buys the whole market”. Tens of studies have now been published in forest trees showing that GS matches or surpasses the performance of phenotypic selection for growth and wood properties traits, enhancing the rate of genetic gain per unit time by increasing selection intensity, radically reducing generation interval and improving the accuracy of breeding values. Breeder-friendly and cost-effective SNP (single nucleotide polymorphism) genotyping platforms are now available for all mainstream plantation forest trees, but methods based on low-pass whole genome sequencing with imputation might further reduce genotyping costs. In this perspective, I provide answers to why GS will soon become the most efficient and effective way to carry out advanced tree breeding, and outline a simple pilot demonstration project that tree breeders can propose in their organization. While the fundamental properties of GS in tree breeding are now solidly established, strategic, logistics and financial aspects for the optimized adoption of GS are now the focus of attentions towards the plateau of productivity in the cycle, when this new breeding method will become fully established into routine tree improvement.