Multivariate models improve accuracy of genomic prediction for spring frost tolerance in Norway spruce. Aro, T., Tan, B., Chen, Z., Hallingbäck, H., Suontama, M., Westin, J., Wu, H., & Hurry, V. The Plant Genome, 18(4):e70151, 2025. _eprint: https://acsess.onlinelibrary.wiley.com/doi/pdf/10.1002/tpg2.70151![Multivariate models improve accuracy of genomic prediction for spring frost tolerance in Norway spruce [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Warming spring temperatures increase the risk of frost damage to emerging Norway spruce (Picea abies) buds by advancing their spring phenology and increasing the frost event frequency. We present a field-based electrolyte leakage assay to assess basal frost tolerance in newly emerging buds. Using this assay, we estimated genetic parameters and tested the effectiveness of multivariate genomic selection (GS) models integrating frost tolerance, bud burst phenology, and height growth. Multivariate models significantly improved frost tolerance prediction accuracy, particularly when incorporating bud burst data, due to a strong genetic correlation between traits (r ≈ –0.63) and high heritability of bud burst (h2 ≈ 0.60). The observed genetic correlations suggest that early-flushing genotypes exhibit higher tolerance to spring frost. Our findings underscore the importance of basal frost tolerance as a complementary trait to traditional phenological frost-avoidance strategies. Additionally, we emphasize that early-stage bud burst assessments in controlled environments can accelerate genomic predictions, overcoming the limitations imposed by long growth cycles. Integrating multi-trait genomic prediction models optimized with bud burst as an assisting trait and optimized model parameters enhances prediction accuracy of spring frost tolerance and supports the development of climate-resilient breeding strategies in Norway spruce.
@article{aro_multivariate_2025,
title = {Multivariate models improve accuracy of genomic prediction for spring frost tolerance in {Norway} spruce},
volume = {18},
copyright = {© 2025 The Author(s). The Plant Genome published by Wiley Periodicals LLC on behalf of Crop Science Society of America.},
issn = {1940-3372},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/tpg2.70151},
doi = {10.1002/tpg2.70151},
abstract = {Warming spring temperatures increase the risk of frost damage to emerging Norway spruce (Picea abies) buds by advancing their spring phenology and increasing the frost event frequency. We present a field-based electrolyte leakage assay to assess basal frost tolerance in newly emerging buds. Using this assay, we estimated genetic parameters and tested the effectiveness of multivariate genomic selection (GS) models integrating frost tolerance, bud burst phenology, and height growth. Multivariate models significantly improved frost tolerance prediction accuracy, particularly when incorporating bud burst data, due to a strong genetic correlation between traits (r ≈ –0.63) and high heritability of bud burst (h2 ≈ 0.60). The observed genetic correlations suggest that early-flushing genotypes exhibit higher tolerance to spring frost. Our findings underscore the importance of basal frost tolerance as a complementary trait to traditional phenological frost-avoidance strategies. Additionally, we emphasize that early-stage bud burst assessments in controlled environments can accelerate genomic predictions, overcoming the limitations imposed by long growth cycles. Integrating multi-trait genomic prediction models optimized with bud burst as an assisting trait and optimized model parameters enhances prediction accuracy of spring frost tolerance and supports the development of climate-resilient breeding strategies in Norway spruce.},
language = {en},
number = {4},
urldate = {2025-11-28},
journal = {The Plant Genome},
author = {Aro, Tuuli and Tan, Biyue and Chen, Zhi-Qiang and Hallingbäck, Henrik and Suontama, Mari and Westin, Johan and Wu, Harry and Hurry, Vaughan},
year = {2025},
note = {\_eprint: https://acsess.onlinelibrary.wiley.com/doi/pdf/10.1002/tpg2.70151},
pages = {e70151},
}
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We present a field-based electrolyte leakage assay to assess basal frost tolerance in newly emerging buds. Using this assay, we estimated genetic parameters and tested the effectiveness of multivariate genomic selection (GS) models integrating frost tolerance, bud burst phenology, and height growth. Multivariate models significantly improved frost tolerance prediction accuracy, particularly when incorporating bud burst data, due to a strong genetic correlation between traits (r ≈ –0.63) and high heritability of bud burst (h2 ≈ 0.60). The observed genetic correlations suggest that early-flushing genotypes exhibit higher tolerance to spring frost. Our findings underscore the importance of basal frost tolerance as a complementary trait to traditional phenological frost-avoidance strategies. Additionally, we emphasize that early-stage bud burst assessments in controlled environments can accelerate genomic predictions, overcoming the limitations imposed by long growth cycles. 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The Plant Genome published by Wiley Periodicals LLC on behalf of Crop Science Society of America.},\n\tissn = {1940-3372},\n\turl = {https://onlinelibrary.wiley.com/doi/abs/10.1002/tpg2.70151},\n\tdoi = {10.1002/tpg2.70151},\n\tabstract = {Warming spring temperatures increase the risk of frost damage to emerging Norway spruce (Picea abies) buds by advancing their spring phenology and increasing the frost event frequency. We present a field-based electrolyte leakage assay to assess basal frost tolerance in newly emerging buds. Using this assay, we estimated genetic parameters and tested the effectiveness of multivariate genomic selection (GS) models integrating frost tolerance, bud burst phenology, and height growth. Multivariate models significantly improved frost tolerance prediction accuracy, particularly when incorporating bud burst data, due to a strong genetic correlation between traits (r ≈ –0.63) and high heritability of bud burst (h2 ≈ 0.60). 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