Development and validation of genomic-assisted breeding models for increased productivity and wood quality of black spruce in Ontario, Canada

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The objective of the proposed research is to develop and test genomic selection models to improve the growth and wood quality of black spruce in northwestern Ontario. Black spruce is one of the most abundant and widely planted tree species in the boreal forest of Canada and is of great economic value to Canada's forest products sector. Traditional tree improvement programs for black spruce in Ontario have produced modest gains in growth but take long periods of time to achieve. Here, we propose to test the application of a relatively new approach to improved breeding, termed genomic selection, to increase the growth per unit time that can be achieved for Ontario's black spruce breeding programs. We will collect data on tree growth and wood quality to estimate the pedigree-based genetic worth of individuals in an existing black spruce breeding program in Ontario and test the accuracy of those models when applied to more advanced generation test populations. This study will be the first proposed to evaluate the accuracy of genomic selection applied to an operational breeding program of black spruce in Ontario. The development of a genomic selection model will enable the rapid identification of individual trees with superior genotypes for wood quality and growth traits, providing a much shorter time to operational seed supply. Project partners will utilize the information gained from this study to identify genetically superior individuals that can form the basis of advanced generation breeding programs. Increases in forest productivity expected to result from this study will benefit Canadians by contributing to the economic growth of the forest industry and by helping to mitigate climate change through increased carbon sequestration.