Abstract

Trees have long life cycles and become reproductively active only after several years. The progress of tree breeding programs is therefore strongly dependent on the time needed to complete a breeding generation. Additionally, the uncertainties associated with conducting decade-long breeding programs can be high. The convergence of genomics and quantitative genetics has now established the paradigm of genomic selection as a way to accelerate breeding of complex traits. With the progressive accumulation of GS data for thousands of individuals across several unrelated populations, GS should also provide a potentially powerful framework to investigate the molecular underpinnings of complex traits. Genomic selection can increase the rate of genetic gain per unit time of a tree breeding program by radically reducing the generation interval and by increasing the selection intensity because many more young seedlings can be genotyped and their phenotypes predicted than the number of adult trees measured in field trials. Genomic selection has therefore become a hot topic in the tree genetics and breeding community worldwide in the last few years since the first perspectives based on simulations and experimental results were reported. In this chapter, a comprehensive discussion is presented, covering the main factors, both theoretical and practical, relevant to the application of GS to tree breeding, including those that have emerged from the recent flow of experimental studies in different forest tree species. Following a review of the basic insights and perspectives of GS, a detailed compilation is presented of all published experimental GS studies in forest trees to date, highlighting their main contributions to our current understanding of this new breeding approach. The conclusion summarizes the main lessons learned so far, condensed in a nine-point tentative roadmap for implementing GS in a tree breeding program.

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