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Implications of accounting for marker-based population structure in the quantitative genetic evaluation of genetic parameters related to growth and wood properties in Norway spruce
SLU Swedish University of Agricultural Sciences, Sweden.
Skogforsk, Sweden.
IIC, Sweden.
RISE Research Institutes of Sweden, Bioeconomy and Health, Pulp, Paper and Packaging.ORCID iD: 0000-0001-5287-3629
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2024 (English)In: BMC Genomic Data, ISSN 2730-6844, Vol. 25, no 1, article id 60Article in journal (Refereed) Published
Abstract [en]

Background: Forest geneticists typically use provenances to account for population differences in their improvement schemes; however, the historical records of the imported materials might not be very precise or well-aligned with the genetic clusters derived from advanced molecular techniques. The main objective of this study was to assess the impact of marker-based population structure on genetic parameter estimates related to growth and wood properties and their trade-offs in Norway spruce, by either incorporating it as a fixed effect (model-A) or excluding it entirely from the analysis (model-B). Results: Our results indicate that models incorporating population structure significantly reduce estimates of additive genetic variance, resulting in substantial reduction of narrow-sense heritability. However, these models considerably improve prediction accuracies. This was particularly significant for growth and solid-wood properties, which showed to have the highest population genetic differentiation (QST) among the studied traits. Additionally, although the pattern of correlations remained similar across the models, their magnitude was slightly lower for models that included population structure as a fixed effect. This suggests that selection, consistently performed within populations, might be less affected by unfavourable genetic correlations compared to mass selection conducted without pedigree restrictions. Conclusion: We conclude that the results of models properly accounting for population structure are more accurate and less biased compared to those neglecting this effect. This might have practical implications for breeders and forest managers where, decisions based on imprecise selections can pose a high risk to economic efficiency.

Place, publisher, year, edition, pages
BioMed Central Ltd , 2024. Vol. 25, no 1, article id 60
Keywords [en]
Genetic Markers; Genetic Variation; Genetics, Population; Models, Genetic; Picea; Wood; article; cross validation; economic efficiency; forest; genetic correlation; genetic parameters; genetic variability; geneticist; heritability; Norway spruce; pedigree; population structure; prediction; quantitative sensory testing; wood; biological model; genetic marker; genetic variation; genetics; growth, development and aging; population genetics; procedures; spruce
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:ri:diva-73762DOI: 10.1186/s12863-024-01241-xScopus ID: 2-s2.0-85195984282OAI: oai:DiVA.org:ri-73762DiVA, id: diva2:1878028
Note

This study was funded by the EU project Assess4EST under ForestValue with grant number Forestvalue_JC2021_JES_087

Available from: 2024-06-26 Created: 2024-06-26 Last updated: 2025-09-23Bibliographically approved

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Grahn, ThomasScheepers, GerhardNordström, Peter

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CiteExportLink to record
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