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

开发和验证基因组辅助育种模型，以提高加拿大安大略省黑云杉的生产力和木材质量

• 批准号: 548769-2020
• 负责人: Thomson, Ashley
• 金额: $ 0.85万
• 依托单位: Lakehead University
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=721064
• 关键词: Development; validation; genomic; assisted; breeding

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.

拟议的研究的目的是开发和测试基因组选择模型，以改善安大略省西北部黑云杉的生长和木质质量。黑云杉是加拿大北方森林中最丰富，种植的树种之一，对加拿大的森林产品部门具有巨大的经济价值。安大略省黑云杉的传统树木改善计划在增长方面取得了适度的增长，但需要很长时间才能实现。在这里，我们建议测试一种相对较新的方法来改善育种（称为基因组选择），以增加安大略省黑色云杉育种计划可以实现的每时间增长。我们将收集有关树木生长和木质质量的数据，以估计安大略省现有的黑云杉繁殖计划中基于血统的遗传价值，并在应用于更高级生成测试人群时测试这些模型的准确性。这项研究将是首次提出的，以评估适用于安大略省黑云杉的运营育种程序的基因组选择的准确性。基因组选择模型的开发将使能够快速识别具有较高基因型的单个树木，以造成木材质量和生长特征，从而提供了较短的运营种子供应时间。项目合作伙伴将利用从这项研究中获得的信息来确定可以构成高级一代育种计划的基础的遗传优越人物。这项研究预期的森林生产率提高将通过为森林工业的经济增长做出贡献，并通过增加碳固换来帮助缓解气候变化，从而使加拿大人受益。