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  • Funder: UKRI Project Code: BB/P020488/1
    Funder Contribution: 784,409 GBP
    Partners: BSW Timber Plc, Maelor Forest Nurseries Ltd, Sitka Spruce Breeding Co-operative, Forestart, Scottish Woodlands, University of Oxford

    BACKGROUND - Selective breeding has increased Sitka spruce yields by 25% in the UK since 1970 but it takes 30 years to genetically select and mass produce new tree varieties. Genomic prediction methods could shorten the process down to 11 years and thus theoretically increase the rate gain from 0.83% to 1.85% per year. Such an acceleration would also enable more timely responses to new challenges such as emerging pests and climate change. The principle is simple: use DNA markers to predict the genetic worth - also called breeding value - which are the data that breeders need most for effective selection. GOALS - We propose to develop genomic prediction in Sitka spruce, the UK's third largest crop by area. Research indicates that models developed from DNA markers can predict breeding value in trees but significant knowledge gaps and model development challenges have prevented practical application. We aim to unlock the potential of genomic prediction by improving our understanding of the relationship between prediction accuracy and population structure, modelling several traits simultaneously and optimizing genotype imputation methods. SPECIFIC OBJECTIVES - We will specifically target productivity and insect resistance traits that we will analyse in a same training population developed from the breeding program and established on two sites, working collaboratively with researchers in the Spruce-up project. The proposed research will develop large-scale genotyping capacity, a genetic linkage map for Sitka spruce and a virtual Pinaceae genome map to support genomic prediction and comparative genomics research. The RESEARCH OBJECTIVES are: 1. Develop a sequence diversity analysis platform and use it to construct genome maps. 2. Develop a predictive genomics platform to target yield improvements and decreased time to harvest. 3. Develop approaches for insect resistance breeding and genetic diversity management. Two major PARTNERSHIP OBJECTIVES will support research excellence and impacts. 4. Transfer knowledge and practice to forestry end-users. 5. Develop an international partnership with the Spruce-up project in Canada. IMPACTS - The methods of predictive genomics and the knowledge developed in this project will benefit the forest industry in three ways: a major acceleration of genetic gains; shorter production time aiming to grow trees and produce the same quality wood in 33% less time; and increased resistance against damaging insect pests. These changes would be transformative for the UK's £2bn per annum forest industry, and lead to more sustainable production, i.e. adapting commercial forests for climate change and mitigating risks of yield losses from newly arrived pests. Our project will link with existing industry networks to translate these changes into benefits for years to come. The impacts could be large in economic terms as commercial Sitka spruce production is valued at around £ 1 billion annually, and in land-use scale as it covers 2.7% of Britain's land area. The novel capacity and know-how from this research will also accelerate developments in other species and will fill gaps in training and expertise of significance to industry and governments globally. TEAM - The project team is made up of internationally renowned academics in the field of genomics at the Universities of Oxford and Edinburgh together with Britain's conifer breeding and crop quality experts based in Forest Research. It combines a uniquely appropriate set of experiences for developing genomics informed tree breeding in the UK. INDUSTRY SUPPORT - The industrial partners for this project are BSW Timber Ltd, Maelor Forest Nurseries Ltd, Forestart Ltd, The Sitka Spruce Breeding Cooperative Ltd, and Scottish Woodlands Ltd. Collectively, these organisations encompass nurseries, tree growing and wood processing, representing the key links in the forestry value chain.